ZIMBABWE VULNERABILITY ASSESSMENT COMMITTEE (ZIMVAC) 2020 RURAL LIVELIHOODS ASSESSMENT REPORT
Mashonaland West Province
ZimVAC is coordinated by the Food and Nutrition Council (FNC) housed at SIRDC: 1574 Alpes Road, Hatcliffe, Harare Tel: +263-242-862586/ +263-242-862025. Website: www.fnc.org.zw. Email: [email protected] Twitter: @FNCZimbabwe. Instagram: fnc_zim. Facebook: @FNCZimbabwe. Foreword
The Zimbabwe Vulnerability Assessment Committee (ZimVAC) under the coordination of the Food and Nutrition Council, successfully undertook the 2020 Rural Livelihoods Assessment (RLA), the 20th since its inception. ZimVAC is a technical advisory committee comprised of representatives from Government, Development Partners, UN, NGOs, Technical Agencies and the Academia. In its endeavour to ‘promote and ensure adequate food and nutrition security for all people at all times’, the Government of Zimbabwe has continued to exhibit its commitment for reducing food and nutrition insecurity, poverty and improving livelihoods amongst the vulnerable populations in Zimbabwe through operationalization of Commitment 6 of the Food and Nutrition Security Policy (FNSP).
As the country is grappling with the COVID-19 pandemic, this assessment was undertaken at an opportune time as there was an increasing need to urgently collect up to date food and nutrition security data to effectively support the planning and implementation of actions in a timely and responsive manner. The findings from the RLA will also go a long way in providing local insights into the full impact of the Corona virus on food and nutrition security in this country as the spread of the virus continues to evolve differently by continent and by country. In addition, the data will be of great use to Government, development partners, programme planners and communities in the recovery from the pandemic, providing timely information and helping monitor, prepare for, and respond to COVID-19 and any similar future pandemics. Thematic areas covered in this report include the following: education, food and income sources, income levels, expenditure patterns and food security, COVID-19 and gender based violence, among other issues.
We want to applaud the ZimVAC as well as the food and nutrition security structures at both provincial and district levels for successfully carrying out the survey during this unprecedented time. In spite of the apparent risks, they exhibited great commitment towards ensuring that every Zimbabwean remains free from hunger and malnutrition. We also extend our appreciation to Government and Development Partners for the financial support and technical leadership which made the assessment a resounding success. The collaboration of the rural communities of Zimbabwe as well as the rural local authorities is sincerely appreciated. The leadership, coordination and management of the whole assessment displayed by the staff at the Food and Nutrition Council (FNC) is also greatly appreciated.
We submit this report to you for your use and reference in your invaluable work. We hope it will light your way as you search for lasting measures in addressing priority issues keeping many of our rural households vulnerable to food and nutrition insecurity. George D. Kembo (DR.) FNC Director/ ZimVAC Chairperson 2 Table of Contents Foreword ………………………………………………………………………………………………………………………………………………………………………………………………..…………..…………..……………………………………………….…..2 Acknowledgements ………………………………………………………………………………………………………………………………………………………..…………………………..…………..……………………………………………….…….….…4 Acronyms ………………………………………………………………………………………………………………………………………………………………………………………………..…………..………………………………………………..…………..…..6 Background and Introduction ………………………………………………………………………………………………………………………………………………………………..…………..………………….……………………..………………………7 Assessment Purpose ……………………………………………………………………………………………………………………………………………………………………………..…………..………………………………………………..……………..11 Assessment Methodology ……………………………………………………………………………………………………………………………………………………………………..…………..……………………………………………..………………..18 Demographic Description of the Sample ……………………………………………………………………………………………………………………………………………..…………..…………………………………………..………………………28 Education ……………………………………………………………………………………………………………………………………...... …………………………………..…………..……………………………………………..…………………….…36 Chronic Illness…………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………38 Social Protection …………………………………………………………………………………………………………………………………………………………………………………..…………..…………………………………………..…………………..…47 Agricultural Production ……………………………………………………………………………………………………………………..……………………………………..…………..………………………………………………..………………………….52 Incomes and Expenditure ……………………………………………………..……………………………………………….………………………………………..…………..……………………………………………..…………………..……………….87 Water, Sanitation and Hygiene ……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….93 Access to Services and Infrastructure…………………………………………………………………………………………………………………………………………………………………………………………………………………………………...112 ISALS and Loans……………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………120 Food Consumption Patterns…………………………………………………………………….……………..……..………………………………………………………..…………..……………………………..……….………………………………………125 Livelihoods Based Coping Strategies ………………………………………………………………………………………………………………………………………………………..…………..…………………………………………..……………….…135 Complementary Feeding ………………………………………………………………………………………………………………………………………………………..…………..…………………………………………..…………………..……………….154 Child Nutrition Status………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………….…159 Gender Based Violence…………………………………………………………………………………………………………………………………………………. ……………………………………………………………………………………………………..163 COVID-19 and Livelihoods………………………………………………………………………………………………………………….…………………………….………………………. ………………………………………………………………………….170 Shocks and Stressors……………………………………………………………………………………………….……………..……..…………………………………………………………..…………..………………………..…..………………………………184 Food Security…………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………………190 Conclusions and Recommendations …..…………………………………………………………………………………………………..……………………………………………..…………..……………………………………………………....………206
3 Acknowledgements
The technical and financial support received from the following is greatly appreciated: • Mhondoro-Ngezi Rural District Council
• Food and Nutrition Council • Zvimba Rural District Council
• Office of the President and Cabinet • Ministry of Finance and Economic Development
• Office of the Minister of State for Provincial Affairs, Mash West Province • Ministry of Justice
• Office of the Provincial Development Coordinator • United Nations Development Programme (UNDP-ZRBF)
• Ministry of Health and Child Care • OXFAM
• Ministry of Lands, Agriculture, Water and Rural Resettlement • UNFPA
• Ministry of Primary and Secondary Education • UNWOMEN
• Ministry of Local Government and Public Works • United States Agency for International Development (USAID)
• Ministry of Public Service, Labour and Social Welfare • Food and Agriculture Organization (FAO)
• Chegutu Rural District Council • United Nations Children’s Fund (UNICEF)
• Hurungwe Rural District Council • World Food Programme (WFP) • Sanyati Rural District Council • Zimbabwe National Statistics Agency (ZIMSTAT) Acknowledgement of Support
ZIMBABWE
5 Acronyms
EA Enumeration Area
FNC Food and Nutrition Council
FNSP Food and Nutrition Security Policy
FNSIS Food and Nutrition Security Information System
HDDS Household Dietary Diversity Score
HHS Household Hunger Score
NNS National Nutrition Survey
RLA Rural Livelihoods Assessment
SAM Severe Acute Malnutrition
TSP Transitional Stabilisation Programme
ZimVAC Zimbabwe Vulnerability Assessment Committee
6 Background and Introduction
7 Introduction
• ZimVAC livelihood assessments’ results continue to be an important tool for informing and guiding policies and programmes that respond to the prevailing food and nutrition security situation. To date, 20 rural and 6 urban livelihoods updates have been produced.
• ZimVAC plays a significant role in fulfilling Commitment Six, of the Food and Nutrition Security Policy (FNSP) (GoZ, 2012), in which the “Government of Zimbabwe is committed to ensuring a national integrated food and nutrition security information system that provides timely and reliable information on the food and nutrition security situation and the effectiveness of programmes and informs decision-making”.
• It has become mandatory for FNC to coordinate annual livelihood updates with the technical support of ZimVAC.
8 Zimbabwe Vulnerability Assessment Committee (ZimVAC)
ZimVAC is a consortium of Government, Development Partners, UN, NGOs, Technical Agencies and the Academia. It was established in 2002 and is led and regulated by Government. It is chaired by FNC, a department in the Office of the President and Cabinet whose mandate is to promote a multi-sectoral response to food insecurity and nutrition problems in a manner that ensures that every Zimbabwean is free from hunger and malnutrition.
ZimVAC supports Government, particularly FNC in:
• Convening and coordinating national food and nutrition security issues in Zimbabwe
• Charting a practical way forward for fulfilling legal and existing policy commitments in food and nutrition security
• Advising Government on the strategic direction in food and nutrition security
• Undertaking a “watchdog role” and supporting and facilitating action to ensure sector commitments in food and nutrition are kept on track through a number of core functions such as:
▪ Undertaking food and nutrition assessments, analysis and research;
▪ Promoting multi-sectoral and innovative approaches for addressing food and nutrition insecurity, and:
▪ Supporting and building national capacity for food and nutrition security including at sub-national levels. 9 Assessment Rationale
The 2020 RLA was undertaken to guide the following:
• Evidence based planning and programming.
• Early warning for early action.
• Evaluation of the socio-economic impact of the COVID-19 pandemic.
• Monitoring and reporting towards commitments made within the guiding frameworks of existing national food and nutrition policies and strategies (TSP, FNSP, Zero Hunger strategy and the SDGs.
• Development of the National Development strategy and the Food and Nutrition Security Strategy, for the next five years.
• The rapidly evolving food and nutrition security situation which was feared to be further deteriorating since the beginning of the COVID-19 crisis in Zimbabwe in April 2020 called for collection of additional and up to date FNS data.
• The current seasonal analysis could not rely on data collected in February 2020 prior to the COVID-19 crisis.
• The survey was envisioned to support the setting-up of the food and nutrition security near real time monitoring and capacitation of sub-national Food and Nutrition Security Committees.
10 Purpose
The overall purpose of the assessment was to provide an annual update on livelihoods in Zimbabwe’s rural areas, for the purposes of informing policy formulation and programming appropriate interventions.
11 Objectives The specific objectives of the assessment were:
1. To assess impact and severity of both Drought and COVID 19 on rural livelihoods. 2. To estimate the population that is likely to be food insecure in the 2020/21 consumption year, their geographic distribution and the severity of their food insecurity 3. To assess the nutrition status of children of 6 – 59 months. 4. To describe the socio-economic profiles of rural households in terms of such characteristics as their demographics, access to basic services (education, health services, protection services and water and sanitation facilities), assets, income sources, incomes and expenditure patterns, food consumption patterns and consumption coping strategies. 5. To determine the coverage (accessibility, availability and quality) of humanitarian and developmental interventions in the country. 6. To determine the effects of shocks experienced by communities on food and nutrition security. 7. To measure resilience at all levels and identify constraints to improving their resilience. 8. To identify early recovery needs in order to determine short to long term recovery strategies. 9. To assess the medium and long term (future) sources of vulnerability and risks to food and nutrition security.
12 Background
• The 2020 RLA was undertaken against a continuously evolving food and nutrition security situation. The performance of the agricultural season negated by the consecutive drought, coupled with the COVID -19 pandemic have affected the livelihoods of the rural and urban population.
• COVID-19, declared a pandemic on 11 March 2020, has literally turned the world ‘upside down’ since it started in Wuhan, China with global reported cases of more than 21 million and more than 760, 000 deaths (14 August 2020).
• The Government of Zimbabwe, responded to the pandemic by gazetting Statutory Instrument 83 of 2020 Public Health (COVID-19 Prevention, Containment and Treatment) Order 2020, on March 27, 2020 declaring the COVID-19 crisis a “national disaster” and introduced a nationwide lockdown with the aim of slowing down the spread of COVID-19.
• The lockdown indicated that essential industries and services needed to remain open to support the health sector and ensure minimal disruption in critical goods and services. During the lockdown the public was strongly encouraged to stay in their homes and to practice social distancing, among other critical preventative measures outlined.
• Prior to the COVID-19 pandemic, food insecurity in the Southern African region was already alarmingly high, with a record 45 million food insecure people across the SADC countries. Key drivers of this food insecurity include climatic shocks (drought, flooding) and structural macro-economic and social factors.
• The risks which threaten to exacerbate the precarious food security situation through the following:
- impacts on exports, imports (supply chain of essential goods such as food, medicine and other essential supplies such as seeds and fertilizers),
- livelihoods (employment and income reduction) and fiscal pressure on the health sector.
- the downstream impact of policy interventions and regulations being implemented to control the spread of COVID-19 which will be felt at individual, household, community and national levels.
• The COVID-19 outbreak and its debilitating impacts on livelihoods will further exacerbate the situation, eroding community coping capacities and deepening food and nutrition insecurity of vulnerable households and individuals.
• Furthermore, we are likely to see an increase in the number of vulnerable people as those who typically are able to cope may find themselves struggling to meet needs given the unprecedented challenging environment.
13 Background
• Impact on Trade
- immediate impact of COVID-19 being realized through its impact on trade.
- Zimbabwe being hit by a drop in export revenues due to slow-down in demand and weakening of its currency.
- On the import side, Zimbabwe with high food import burden will be affected.
- The decision for lockdown is needed for reducing infection and “flattening the curve” but has far reaching effects on people and their livelihoods, especially of daily wage earners, small businesses, the informal sector and the large population already at risk because of pre-existing vulnerability conditions.
14 Background
• Impact on Programme and Supply Chain
- Requirements to maintain social/physical distancing and travel restrictions are negatively impacting programme delivery and humanitarian and developmental activities, which threatens food and nutrition security.
- Travel restrictions and border closures are likely to delay the movement of the essential supplies such as seed and fertilizers (for the winter season) which are crucial for the preparation for the 2020/2021 planting season. This could have longer-term implications on the food security of households.
• Programmes will inherently have to depend on reduced information and evidence.
15 Background
• COVID-19 Effect on Populations
- There is a high likelihood that urban areas are at the highest risk because of high density settlements as they are also the main entry points for international travel. The population group most affected would include the urban poor and the daily wage employees whose livelihoods are curtailed by the lockdown measures.
- The disruption of supplies of agricultural inputs is likely to affect the preparations for the next agricultural season which is very much needed to start the recovery from the back-to-back droughts that have been experienced so far and affect farmers’ livelihoods.
- Markets play a major role in enhancing food and nutrition security. However, market dynamics, failures and shortcomings often weaken the desired impacts and long term effects. Furthermore, households with livelihood options such as petty trade, vending, casual labour, skilled trade and own businesses were likely to experience the most impact of no trade during the lockdown period.
16 Background • Poverty continues to be one of the major underlying causes of vulnerability to food and nutrition insecurity as well as precarious livelihoods in Zimbabwe. According to the ZIMSTAT Poverty, Income, Consumption and Expenditure Survey 2017 Report, 70.5% of the population were poor whilst 29.3% were deemed extremely poor.
• The projected GDP growth rate for 2019 was -6.5% and 3% for 2020.
• Year on year inflation for May 2020 was at 785.55%.
• The Total Consumption Poverty Line (TCPL) for April 2020 was ZWL 7,425.81 which is 703.4% higher compared to the same time last year.
• The impact of poor rainfall distribution was compounded by the unaffordability of key agricultural inputs such as seed, fertilisers and herbicides. Consequently, the area planted to major crops in the 2019/20 season was lower in most areas compared to the same time in the previous season.
17 Assessment Methodology
18 Methodology – Assessment Design
• The assessment was a cross-sectional study whose design was guided and informed by the Food and Nutrition Security Conceptual framework (Figure 1), which Zimbabwe adopted in the FNSP (GoZ, 2012), and the conceptual framework on food security dimensions propounded by Jones et al. (2013) . • The assessment was also guided and informed by the resilience framework (figure 2) so as to influence the early recovery of households affected by various shocks. • The assessment looked at food availability and access as pillars that have confounding effects on food security as defined in the FNSP (GoZ, 2012). • Accordingly, the assessment measured the amount of energy available to a household from all its potential sources hence the primary sampling unit for the Figure 1: Food and Nutrition Conceptual Framework assessment was the household.
19 Figure 2: Zimbabwe resilience framework (UNDP Zimbabwe, 2015)
20 Methodology – Assessment Process
• ZimVAC, through multi-stakeholder consultations, developed an appropriate assessment design concept note and data collection tools informed by the assessment objectives.
• The primary data collection tools used in the assessment were the android–based structured household tool and the District key informant tool.
• ZimVAC national supervisors (including Provincial Agritex Extension Officers and Provincial Nutritionists) and enumerators were recruited from Government, United Nations, Technical partners and Non-Governmental Organisations. These underwent training in all aspects of the assessment. In order to minimise risk of spreading COVID-19, training for both supervisors and enumerators was done virtually.
• The Ministry of Health and Child Care was the lead ministry in the development of the Infection, Prevention and Control (IPC) guidelines for the assessment. These were used to train all enumerators and supervisors on how to practice IPC measures during the whole assessment process.
• The Ministry of Local Government, through the Provincial Development Coordinators’ offices coordinated the recruitment of district level enumerators and mobilisation of provincial and district enumeration vehicles. Enumerators for the current assessment were drawn from an already existing database of those who participated in one or two previous ZimVAC 21 assessments. Four enumerators were selected from each district for data collection. Methodology – Assessment Process
• Primary data collection took place from 11 to 25 July, 2020. In recognising the risk of spreading COVID-19 during data collection, innovative approaches were used to collect vital information without causing any harm. The RLA was guided by global and country specific recommendations and all necessary precautions were taken to avoid potential transmission of COVID-19 between enumerators and community members. In order to reduce exposure to COVID-19 through person to person physical contact, primary caregivers were capacitated to measure their children using Mid-Upper Arm Circumference (MUAC) tapes and assessment of oedema.
• Data analysis and report writing ran from 27 July to 21 August 2020. Various secondary data sources and field observations were used to contextualise the analysis and reporting.
22 Methodology - Sampling and Sample Size
• Household food insecurity prevalence was used as the key indicator to determine the sample to ensure 95% confidence level of statistical representativeness at district, provincial and national Number of Sampled level. District Households • The survey collected data from 20 randomly selected enumeration areas (EAs) that were Chegutu 199 enumerated in the 2019 RLA. • A two staged cluster sampling was used and comprised of; Hurungwe 200 • Sampling of 20 clusters per each of the 60 rural districts, denoted as EAs in this assessment, from the Zimbabwe Statistics Agency (ZIMSTAT) 2012 master sampling frame Kariba 200 using the PPS methodology • The second stage involved the systematic random sampling of 10 households per EA (village). Makonde 195 Selection of Households for the “Panel” survey: From a selected village, a list of the households that were interviewed during the 2019 survey was created and 5 households selected using Zvimba 199 systematic random sampling. Household data interviews were conducted in the sampled households. Mhondoro-Ngezi 199
Selection of Non-Panel Households: From the same randomly selected village a household list of non-panel households from the village head was generated and the remaining number of households (5) from the sample was identified using systematic random sampling. Sanyati 200
• A total of 200 households were interviewed per district, bringing the total sampled households Province 1392 to 1392.
23 Methodology – Sampled Wards
24 Data Preparation and Analysis
• Primary data was transcribed using CSEntry on android gadgets and using CSPro, it was consolidated and converted into SPSS, STATA and DBF datasets for: • Household structured interviews • District key informant Focus Group Discussion (transcribed in excel)
• Data cleaning and analysis were done using SPSS, STATA, ENA, Microsoft Excel and GIS packages.
• Analyses of the different thematic areas covered by the assessment were informed and guided by relevant local and international frameworks, where they exist.
• Gender, as a cross cutting issue, was recognised throughout the analysis.
25 Technical Scope
The 2020 RLA collected and analysed information on the following thematic areas:
• Education • Social Protection
• Health • Markets
• WASH • Gender Based Violence
• Nutrition • COVID-19
• Agriculture and other rural livelihoods activities • Linkages amongst the key sectoral and thematic areas • Food Security • Cross-cutting issues such as gender • Shocks and stressors
26 Assessment Findings
27 Household Demography Characteristics of Household Head: Age
100 90 80 70 60 51 48 50 50 48
50 46 46 48 Years 40 30 20 10 0
• The Provincial household head average age was 48. The average age of household head varied across the district ranging from 46 years to 51 years. Average Household Size
10 9 8 7
6 5.3 4.7 5.0 4.8 4.7 5 4.4 4.5 4.5 Household Size Household 4 3
Average 2 1 0
• The average household size in Mashonaland West is 4.7 Sex of Household Head 100 90 21.5 20.5 24.6 24.0 23.1 25.1 29.1 32.5 80 70 60 50 40 78.5 79.5 75.4 76.0 76.9 74.9 70.9 67.5 30 20
Proportion of Households(%) of Proportion 10 0
Male Female
• Majority of household heads in Mashonaland West were male (74.9 %) as compared to females (25.1%). The picture is almost similar across all the districts. • Kariba had the highest proportion of female headed households (32.5%) when compared to other districts in Mashonaland West province whereas Makonde had the lowest at 20.5%. Child and Elderly Headed Households 50
40 32.7 32.2 31.0 30 26.5 26.8 22.0 23.1 20.0 20
10
Proportion of Households(%) of Proportion 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.1 0
Elderly headed HH Child headed HH
• Chegutu (32.7%), recorded the highest proportion of elderly headed households followed by Mhondoro-Ngezi (32.2%). • Child headed families were recorded only in Zvimba (0.5%). Religion of Household Head
Roman Other Other Catholic Protestant Pentecoast Apostolic Christian Traditional religion No religion (%) (%) al (%) Sect (%) Zion (%) (%) Islam (%) (%) (%) (%) Chegutu 8.1 5.4 23.7 28.0 0.5 7.5 1.1 1.1 0.5 24.2 Hurungwe 3.8 6.5 3.8 29.0 5.9 8.6 2.2 3.8 4.3 32.3 Kariba 4.5 1.1 10.6 31.8 5.6 11.2 0.6 9.5 2.8 22.3 Makonde 3.1 6.2 6.2 28.7 3.1 16.4 1.5 4.1 1.0 29.7 Mhondoro 6.6 9.6 16.2 33.0 5.1 14.2 0.5 0.5 1.0 24.6 -Ngezi Sanyati 5.6 8.6 16.2 33.5 2.5 9.1 0.5 4.1 5.6 13.2 Zvimba 5.5 7.0 11.1 30.2 2.5 8.5 7.5 0.5 2.5 14.2 Province 5.3 6.4 12.5 30.6 3.6 10.8 2.0 3.3 2.5 22.9
• About a third (30.6%) of household heads belong to the Apostolic Sect. Marital Status of Household Head 100 0.0 0.0 1.0 0.5 1.5 2.0 2.0 1.0 15.5 12.9 11.8 90 23.1 16.1 17.4 5.6 22.6 20.0 80 3.5 8.2 2.1 6.5 2.6 4.0 6.0 5.0 5.0 3.02.5 2.0 3.5 4.0 70 8.0 60 50 40 80.0 74.5 75.3 70.4 72.0 72.4 72.6 30 63.8 20 10 Proportion of Household Heads(%)Household of Proportion 0
Married living together Married living apart Divorced/seperated Widow/widower Never married
• The majority of household heads (72.6%) were married and living together with their spouses while 17.4% were widowed. Education of Household Head
100 3.5 2.0 2.0 1.5 1.0 1.5 2.5 2.0 90 25.5 80 32.2 27.5 27.7 34.6 34.8 30.3 30.3 70 16.0 13.5 10.3 10.1 60 12.6 14.7 12.6 12.8 50 40 28.5 32.3 38.5 43.6 38.5 30 46.7 41.4 38.4 20 28.5 10 18.0 16.9 24.7 16.4 5.0 8.4 12.6
Proportion of Household (%) Household of Proportion 0
None Primary level ZJC level O level A level and above
• Majority of the household heads in Mashonaland West Province had attained at least primary school level education (38%). • Kariba had the highest proportion of household heads that did not attend any formal education (29%). Characteristics of Household Head: Nature of Disability
100 90 33.3 80 50.0 50.0 70 60.0 61.2 66.7 60 88.9 50 33.3 12.5 40 16.7 10.0 4.1 30 8.3 10.2 10.0 16.7 20 6.1
16.7 38 33.3 Proportion of Household Heads(%) Household of Proportion 10 20 16.7 18.4 8 11.1 0 Chegutu Hurungwe Kariba Mhondoro-Ngezi Sanyati Zvimba Province
Blind Deaf Wheelchair bound Mental Other
• In Mash West Province, of the household heads that reported that they were physically or mentally challenged, 18.4% were blind, 6.1% were deaf and 10.2% were wheelchair bound. Characteristics of Household Head: Vulnerability Attributes 100 90 80 70 61.2 60 50 40 30
20 Proportion of Households(%) of Proportion 10 3.5 6.0 0 Household head physically/mentally Household head disabled to the extent of Household head chronic illness challenged being unable to work
• Of the 3.5% household heads that were physically /mentally challenged, 61.2% were disabled to the extent of not being able to work. • Six percent of household heads were chronically ill Household Vulnerability Attributes 100 90 80 70 60 50 40 30 20.0 22.0 17.6 16.6 Proportion of Households(%) of Proportion 20 15.5 15.5 13.5 13.6 15.7 11.6 12.6 10.8 9.5 10.0 8.2 7.5 9.5 7.5 8.0 10 6.0 4.6 6.7 6.5 6.5 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Orphan present in HH Mental or physically challenged present in HH Chronically ill present in HH
• Sanyati District had the highest proportion of households with at least an orphaned child (22%). Education Children Sent Away From School due to Non- Payment of Fees 100 90 80 73 70 62 64 58 60 54 55 50 42 40 33 30
20 Proportion of Children(%) of Proportion 10 0
• The proportion of children that were sent away from school due to non payment of fees increased from 43% during first term 2019 to 55% the same period this current year. Reasons For Not Going to School
Expelled from school 0 0 No food at home 0 0.2 Care for ill or disabled household member 0.2 0.3 Covid-19 lockdown 0.5 0.5 Disability 0.8 1 Help with household work 1 1 Other 2.9 4.1 Distance to school to far 4.3 5.8 Not interested in school 5.8 33.8 Expensive or no money 37.7 0 5 10 15 20 25 30 35 40 Proportion of Children (%)
• The major reason why children were out of school was that it was expensive or parents had no money (37.7%) . • Some of the children aged 4-5 years (33.8%) were out of school because they were considered too young by their parents. • Of concern is the proportion of teenage girls not going to school because of pregnancy (5.8%). Children currently receiving any form of schooling (home, online, WhatsApp)
50
40
30
20 14 10 10 7 6 7
Proportion of Children (%) Children of Proportion 5 3 3 0
• Only 7% of children in Mashonaland West province are currently receiving some form of schooling(home online,whatsApp). Chronic illness
• Chronic diseases are defined broadly as conditions that last 1 year or more and require ongoing medical attention or limit activities of daily living or both (CDC). These include diseases such as heart disease and stoke , cancer, diabetes and HIV among others. Food Insecurity is highly associated with chronic illness among the adults. Food insecurity and chronic illness can form a vicious circle with adults living in a food insecure household likely to have chronic illness whereas chronic illness may at the same time result in a household being food insecure. Individuals with Chronic illness 50 45 40 35 30 25 20 15 10 7.6
Proportion of Members(%) of Proportion 5.4 5.2 4.5 3.2 4.1 5 1.4 1.5 0
• Mashonaland West province had 4.1 % of the population with at least one chronic illness. • Zvimba had the highest proportion of individuals with chronic illness at 7.6 %, followed by Chegutu and Mhondoro Ngezi at 5.2 %. Households with Chronically ill Members 50
40
30 30 23 20 18 20 16 14
10 5 6
Proportion of Households(%) of Proportion 0
• At least one household member had chronic illness in 16% of households in Mashonaland West Province. • Zvimba district had the highest proportion of households with chronic ill members(30%) followed by Mhondoro Ngezi (23%). Social Protection Households which Received Support by District
100 90 80 70 70 65 60 61 61 62 61 60 49 50 40 30
Proportion of households (%) households of Proportion 20 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province
• The proportion of households which received support from all possible sources in the form of food, cash, crop inputs ,livestock inputs or WASH was 61%, a decrease from 71% in 2019. Households which Received Support from Different Sources
District Government UN/NGO Church Rural Rural non- Urban Urban non- Diaspora Mutual Civic Charity Women/ men support support support relatives relatives relatives relatives relatives groups groups groups groups Chegutu 46.7 37.7 2.0 12.1 6.0 20.6 1.5 5.0 0.0 0.0 0.0 1.0 Hurungwe 47.0 22.0 2.0 1.0 0.0 5.0 0.5 1.5 0.0 0.0 0.0 0.0 Kariba 35.5 43.0 0.5 3.0 1.5 0.5 0.0 0.0 1.0 0.0 0.0 0.0 Makonde 43.1 19.0 4.1 6.7 2.1 18.5 1.0 2.1 1.0 0.5 0.5 1.5 Mhondoro- Ngezi 55.8 22.6 1.5 9.0 4.0 18.6 2.5 5.5 0.5 0.0 0.0 0.5 Sanyati 44.5 32.0 3.0 4.0 0.5 7.5 2.5 4.0 0.0 0.0 0.0 0.0 Zvimba 35.7 9.0 4.5 5.0 4.0 13.1 1.5 2.0 0.0 0.0 0.5 0.0 Province 44.0 26.5 2.5 5.8 2.6 11.9 1.4 2.9 0.4 0.1 0.1 0.4
• The main sources of support received by households were from the Government(44%), UN/NGO (26.5%) and Urban relatives(11.9%). Forms of Support Received from Government
District Food Cash Crop inputs Livelihoods programming Chegutu 100 0 0 0
Hurungwe 100 0 0 0
Kariba 80 9 2 5
Makonde 100 0 0 0
Mhondoro-Ngezi 94 0 2 4 Sanyati 96 4 0 0
Zvimba 100 0 0 0
Province 96 2 1 1
• The social protection support received by households from the Government came in form of food (96%) Agricultural Production Access to Agricultural Extension Services on Crops
100 95 94 93 91 89 91 90 86 86 80 70 60 50 40 30 20 Proportion of Households (%) Households of Proportion 10 0
• On average, 91% of households received extension advice on crop production, the highest proportion being in Chegutu (94%). Access to Agricultural Extension Services on Livestock
100 90 80 70.8 70 58.2 60 57.1 54 55.9 50.8 50.7 50 44.4 40 30 20 Proportion of Households(%) of Proportion 10 0
• The proportion of households receiving extension advice on livestock production is below 70% for most districts except in Sanyati (70.8%) Households Affected by the Fall Armyworm
100 90 80 70 66 59 60 57 50 40 32 30
20 Proportion of households (%) households of Proportion 10 0 2016/17 2017/18 2018/19 2019/20 • Generally across the province, the proportion of households that reported that their crops were affected by fall armyworm has increased for the past four seasons. Crops Affected by the Fall armyworm 100
90
80
70 66 67
60
50 41 40 32
30 Proportion of households (%) households of Proportion 20 10 11 10 6 7 7 8 3 0 Groundnuts Tubers Roundnuts Tobacco Sugar beans Soya beans Cowpeas Cotton Sorghum Maize Pearl millet
• The most common crops reported to have been affected by Fall armyworm are pearl millet (67%), maize (66%) and sorghum 41%) • Cotton (32%) was also a crop of major agricultural importance which was affected by the pest Time Taken to Control Fall Armyworm 100 90 80 73 69 70 62 60 54 51 50 46 41 39 40 37 37 36 37 30 25 24 23 21 20 20 20 16 17 11 Proportion of households (%) households of Proportion 9 10 6 7 7 2 2 4 1 4 1 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Did nothing Upon identification Within 2 weeks 3-4 weeks
• Only 37% of households implemented control measures on the pest upon identification and 7% took 3-4weeks to implement control measures. • Control measures were taken upon identification highly in Kariba, 69% followed by Chegutu at 62%. Measures Taken to Control Fall Armyworm
Other methods 1
Applied other substances specify 4
Applied commercial pesticides (less than recommended dosage) 4
Applied commercial pesticides (recommended dosage) 21
Applied commercial pesticides (more than recommended dosage) 8
Traditional control (physically picking the pest) 23
Nothing 43
0 10 20 30 40 50 60 70 80 90 100 Proportion of households (%)
• Of the households whose crops were attacked by fall armyworm, about 43% did not take any measures to control the pest • The major control measure taken was physically picking the pest (23%) • Commercial pesticides were applied by 33% of households of which 21% used the recommended dosage Success of Control Measures 100 90 80 76 70 61 63 60 49 52 51 48 50 44 37 38 40 35 33 30 26 30 30 22 23 24 16 20 13 12 14 5 10 0 Proportion of households (%) households of Proportion 0
Extremely successful Somewhat successful Not successful
• About 48% of the households reported that control measures on fall armyworm were not effective, 38% reported that their measures were somewhat successful while only 14% reported extremely successful measures. • The proportion of households whose control measures were not successful was highest in Kariba (76%), Sanyati (63%) and Hurungwe (61%) • Chegutu (49%) had the highest proportion of households whose control measures were extremely successful Crop Production Households which Planted Crops
100 90
80 75 70 60 50 40 30 18
Proportion of Households(%) of Proportion 20 14 14 11 10 6 6 7 2 3 4 0 Wheat Other crops Paprika Pearl millet Finger millet Sunflower Soya beans Sugar beans Roundnuts Tubers Tobacco Cotton Cowpeas Sorghum Groundnuts Maize
• Maize remains the crop grown by the majority of households, with about 75% of households having grown it. • The other cash crops wheat (0%), Tobacco (7%) and Cotton (11%) are being grown by a small proportion of households. Households which Planted Cereals by District
100 91.5 87.5 90 84.4 75.9 80 72.4 74.9 70 64.8 60 47.5 50 40 35.5 30 25.5 20 14.5 13.8 7.7 7.5 Proportion of households(%) of Proportion 10 4.5 1.5 0.0 1.0 0.5 0.5 1.0 1.51.0 0.8 0
Maize Sorghum Finger millet Pearl millet
• Maize and sorghum were the most common cereals planted across all districts. • The proportion of households who planted maize decreased from 85% in the 2018/19 season to 74.9% in the 2019/20 season. • There was an increase in the proportion of households who planted sorghum from 7% in the 2018/19 season to 13.8% in the 2019/20 season. Sources of Inputs for Crops
Proportion of households (%) Government Purchases Retained Carryover Remittances NGO Gifts Private contractors Maize 52 31 17 9 4 2 2 0 Sorghum 33 6 32 15 7 6 8 1 Finger millet 7 6 52 23 8 3 7 0 Pearl millet 17 5 51 20 5 4 8 0 Tubers 0 10 53 31 6 0 7 0 Cowpeas 4 10 46 24 8 5 7 0 Unshelled groundnuts 1 14 54 25 6 1 5 0 Unshelled roundnuts 1 17 48 27 6 0 7 0 Sugar bean 3 40 33 18 6 3 3 1 Soya bean 5 45 30 10 8 0 2 0 Tobacco 1 29 1 1 2 0 1 68 Cotton 59 4 1 2 1 1 1 36
• Government was the major source of inputs for cotton (59%), maize (52%) and sorghum (33%) • Retained seed which negatively impacts on quality and quantity of crop yields , was a main source for small grains , cowpeas, tubers, groundnuts and round nuts. • The main source of inputs for tobacco were the private contractors Average Household Cereal Production by District 900 792 800 700 600 484 500 kgs 400 346 314 300 198 210 200 111 100 70 1 0 3 3 0 20 3 4 0
Maize (in kgs) Small grains (in kgs)
• The highest average maize production was reported in Makonde (792kg) whilst the lowest was recorded in Kariba (70kg) • Sanyati had the highest small grains production, 20kg • Generally across the whole province . a household produced 314kg maize, a decrease from 433.3 kg reported in the 2018/19 season. Average Household Cereal Stocks (kg) as at 1 April 2020
District Maize Sorghum Pearl millets Wheat Rice
Chegutu 65.3 2.7 0.1 0.0 0.2
Hurungwe 58.7 1.7 0.0 0.0 0.0
Kariba 74.4 18.9 0.0 0.0 0.8
Makonde 153.1 0.2 0.0 1.0 0.1
Zvimba 43.7 3.0 0.0 0.0 0.2
Mhondoro-Ngezi 79.8 2.8 0.0 0.0 0.3
Sanyati 130.5 3.6 0.0 1.1 0.4
Province 86.3 4.7 0.0 0.3 0.3
• The average household cereal stocks reported by majority of households was 86.3kg maize and 4.7kg sorghum. Non Timber Forest Products Indigenous Fruits Readily Available and Consumed at District level Chegutu Hurungwe Kariba Makonde Mhondoro Ngezi Sanyati Zvimba
Available Consumed Available Consumed Available Consumed Available Consumed Available Consumed Available Consumed Available Consumed mazhanje 12.4 9.2 32.1 31.4 1.8 0.6 30.4 41.4 3.7 9.2 6.49 3.3 45.3 45.9 meswane 47.7 40.2 41.7 35.1 20.0 16.7 45.5 33.3 48.1 29.9 27.92 29.1 51.6 47.8 nhengeni 4.1 3.8 34.8 32.4 8.2 4.2 17.8 18.8 14.4 10.3 13.64 11.3 6.2 5.7 hacha 47.2 33.2 37.4 36.7 7.6 4.2 41.4 40.9 17.1 16.8 1.30 2.6 44.1 42.1 maonde 1.0 1.6 32.6 30.3 2.4 0.6 8.4 16.1 6.4 4.9 1.30 1.3 1.2 1.9 hubva 59.1 53.8 54.5 48.4 18.2 15.5 23.0 27.4 57.2 50.0 5.19 7.3 41.0 40.9 matohwe 53.4 44.0 52.4 45.2 14.7 7.1 68.6 64.5 58.3 58.2 57.14 57.6 57.1 49.7 nzviru 1.6 0.5 28.9 28.2 4.1 1.2 5.2 13.4 32.1 19.0 0.00 1.3 1.2 0.6 matufu 21.8 12.5 50.8 41.0 3.5 4.2 26.2 29.6 18.2 13.6 7.14 9.3 24.8 18.2 maroro 3.1 1.6 33.7 30.3 4.1 0.6 14.7 19.4 2.7 4.3 1.30 6.6 0.6 1.9 mauyu 1.6 2.2 31.0 30.9 65.3 67.9 3.1 22.0 3.2 7.1 12.99 12.6 0.0 0.6 nyii 11.9 10.3 44.9 37.8 40.6 43.5 25.1 26.9 51.9 52.7 30.52 24.5 3.7 1.3 masawu 7.8 4.3 50.8 42.0 76.5 63.7 26.7 38.2 41.2 39.7 62.34 61.6 15.5 14.5 hute 7.8 4.9 31.0 28.2 4.1 1.8 12.0 23.7 8.0 9.8 0.65 2.0 18.0 15.1 tsambati 8.3 4.3 39.6 30.3 1.2 0.6 29.8 28.5 1.6 0.5 0.65 0.0 2.5 3.1
• Meswane, Hubva , Matohwe and Nhunguru were readily available and commonly consumed at household level across all districts in the province Availability of indigenous vegetables
• Indigenous vegetables are found in all the districts of Mashonaland West province
• Mutsine is found in 60-80% of Hurungwe Makonde, Zvimba, and Mhondoro Ngezi.
• About 60-80% of the all districts have nyevhe Edible Insects Consumed
Harati Harurwa Humbwe Hwiza Ishwa Madora Magandari Majeny (%) (%) (%) (%) (%) (%) (%) a Majuru MakurweMandere Nyenze Tsambarafuta Tsumwarumwa Others Chegutu 5.0 0.8 0.8 33.9 38.0 38.0 0.8 2.5 7.4 17.4 11.6 8.3 16.5 1.7 0.8 Hurungwe 5.3 0.0 0.7 68.7 39.3 25.3 0.7 0.0 38.7 2.7 1.3 1.3 32.0 27.3 1.3 Kariba 0.0 0.0 0.0 71.3 52.9 9.2 6.9 0.0 8.0 6.9 0.0 9.2 6.9 31.0 3.4 Makonde 8.8 1.9 1.3 80.6 65.0 28.1 3.8 0.0 11.3 3.8 3.8 1.9 28.8 25.0 0.0 Mhondoro -Ngezi 1.4 0.0 0.7 32.6 52.9 76.8 5.1 1.4 15.9 7.2 0.0 1.4 13.8 3.6 0.7 Sanyati 2.7 0.9 1.8 57.7 27.0 46.8 7.2 1.8 12.6 2.7 0.0 0.9 7.2 0.0 1.8 Zvimba 6.6 2.8 1.9 84.9 67.9 9.4 0.0 0.0 9.4 3.8 3.8 3.8 22.6 1.9 1.9 Province 4.3 0.9 1.0 61.4 49.0 33.4 3.5 0.8 14.8 6.3 2.9 3.8 18.3 12.9 1.4
• In Mashonaland West, edible insects that were commonly reported to be consumed by household members were Hwiza (61.4%), Ishwa (49%) and Madora (33.4%). Livestock Production Average Livestock Numbers per household
10 9 9 8 7 6 6 6 6 6 6 5 5 5 5 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 2 1 Proportion of Households(%) of Proportion 1 0
cattle Goats Sheep Donkeys
• The average herd size per household was 4, whilst the average goat flock size per household was 6. • Kariba District had the highest number of goats per household (9). Households cattle ownership
100 7 7 13 11 1 13 13 5 10 90 2 4 6 20 3 3 6 7 9 5 4 6 80 6 9 11 3 9 19 4 70 7 6 13 60 50 89 40 77 79 67 72 30 63 65 63 20 Proportion of households (%) households of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Zero One to Two Three to Four Five >Five
• Seventy-Two percent of households in the province do not own cattle. • Zvimba District had the highest proportion of households that do not own cattle Cattle Draught Power Ownership
100 3 7 11 6 8 13 9 90 04 16 15 10 12 10 1 14 80 14 2 11 2 70 7 3 5 60 50 90 94 40 82 79 79 69 68 70 30 20
Proportion of households (%) households of Proportion 10 0
Zero One Two >Two • The majority of households (79%) in the province do not own draught cattle. • Zvimba district had the highest (94%) proportion of households that do not own draught cattle Cattle and Goats Mortality Rates for Period 1 April 2019 to 31 March 2020 100 90 80 70 60 50 40 35.7 34.4 30.5 30 24.0 Mortality rate (%) rate Mortality 16.8 18 20 12.8 7.2 8.1 7.0 10 5.4 4.8 5.0 4.2 3.6 2.6 5.5 5.2 0
cattle mortality rates Goat mortality rates
• Across the whole province , cattle mortality rate was 16.8%, a decrease from 2019 (24%) but remains higher than the acceptable rates of 3-5% • Highest cattle mortalities were recorded in Chegutu (35.7%), Mhondoro-Ngezi (34.4% and Zvimba (30.5%) • The provincial goats mortality rate of 5.2% was below the acceptable rates of 8%-10% Causes of Cattle Deaths
100 6 8 11 6 90 14 20 20 13 80 10 70 60 50 100 71 94 92 89 89 40 75 70 30
20 Proportion of households (%) households of Proportion 10 14 0 5 1 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Drought/Lack of water Diseases Predators Slaughter for own consumption Other
•Across the province ,cattle deaths were mainly due to diseases (89%), • All cattle deaths in Chegutu were due to diseases (100%) •Zvimba district reported the highest proportion of households slaughtering cattle for own consumption(20%) Goats Ownership
100 3 7 6 1 4 90 5 3 16 18 16 5 13 7 12 28 3 5 3 80 7 7 5 9 12 3 9 12 70 13 8 8 60 13 10 6 50 88 40 75 68 66 30 61 60 58 52 20 Proportion of households (%) households of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Zero One to Two Three to Four Five >Five
• The proportion of households which own goats was 34% which is a slight decrease from 36% in 2019 • The highest proportion of households owning goats was in Kariba (48%) and Sanyati (42%) • The lowest proportion of households with goats was in Zvimba (12%) • Kariba (28%) had the highest proportion of households with more than five goats Causes of Goats Deaths 100 90 86 80 75 73 70 69 70 58 60 60 57 50 40 33 30 25 25 17 20 20 20 20 14 13 8 8 12 10 7 7 5 5 Proportion of Households(%) of Proportion 0 0 0 0 0 0 0 0 0
Drought/Lack of water Diseases Predators Slaughter for own consumption Floods/cyclone Other
•Diseases (69%) were the major cause of deaths followed by slaughter for own consumption and predators (13%). •Sanyati (86%)had the highest proportion of households whose goats died of diseases. Households who had cattle deaths (Period 1 April 2019 to 31 March 2020)
100 1.1 4.30.0 1.1 1.0 7.1 9.7 10.9 90 14.9 10.6 21.3 9.7 5.1 80 33.9 33.8 12.9 14.7 70 60 14.5 10.0 50 18.8 16.1 85.1 90.9 40 82.8 76.4 67.7 69.3 30 20 35.5 37.5 Proportion of Households (%) Households of Proportion 10 0
zero one to two three to four Five or more
• Chegutu (33.9%) and Mhondoro Ngezi (33.8%)had the highest proportion of households that reported to have had at least five cattle during the period under review. Agricultural Produce Markets Average Maize Grain Prices by District
Maize Grain Price (ZWL$) Maize Grain Price (USD)
450 402 402 412 402 6 400 381 5 5 5 5 354 5 5 350 4 300 263 4 241 3 250 3 3
200 Price(USD) Price(ZWL) 150 2 100 1 50 0 0
• The highest maize grain prices per 20litre tin were reported in Mhondoro-Ngezi (ZWL$412) followed by Chegutu, Kariba and Sanyati (ZWL$402). • The lowest price was reported in Hurungwe (ZWL$241). • The provincial average price was ZWL$354 . Average Maize Meal Prices by District
500 460 10
400 362 8 322 324 300 282 6 240 6 5 4 4 200 4
4 3
Price (USD) Price Price (ZWL$) Price 100 2
0 0
Kariba
Kariba
Zvimba
Sanyati
Zvimba
Sanyati
Chegutu
Province
Chegutu
Province
Makonde
Makonde
Hurungwe
Hurungwe
Mhondoro-Ngezi Mhondoro-Ngezi
• The highest maize meal prices per 10kg was reported in Zvimba (ZWL$460) followed by Chegutu (ZWL$362). • The lowest price was reported in Kariba (ZWL$240). • Hurungwe and Makonde did not have maize meal on the market in rural areas. • The provincial average price was ZWL$324 . Average Cattle Prices by District
50000 500 45000 432 450 411 40000 400 378 368 372 366 34747 35000 33106 350 30383 29645 29923 29441 301 300 30000 300 24233 24140 25000 250
20000
Price (USD) Price 200 Price (ZWL$) Price 15000 150 10000 100 5000 50 0 0
• The highest cattle price was reported in Kariba (ZWL$34747) followed by Zvimba (ZWL$33106). • The lowest price was reported in Sanyati (ZWL$24140). • The provincial average price increased from ZWL$769 in 2019 to ZWL$29441 in 2020. Average Goat Prices by District
5000 50 4500 45 4000 40 3500 35 34 30 29 28 3000 2713 30 27 25 2414 2329 25 23 2500 2163 2230 2012 1857 20
2000 (USD) Price 17 Price (ZWL$) Price 15 1500 1353 10 1000 5 500 0 0
• The highest goat price was reported in Zvimba (ZWL$2713) followed by Chegutu (ZWL$2414) and Makonde (ZWL$2329)) • The lowest price was reported in Kariba (ZWL$1353) • The provincial average price increased from ZWL$84 in 2019 to ZWL$2230 in 2020 Average Chicken Prices by District
500 10 450 433 9 402 402 402 402 400 383 8 347 350 7 301 300 6 5 5 5 5 5 5 250 5 4 4
200 4
Price (USD) Price Price (ZWL$) Price 150 3 100 2 50 1 0 0
• The highest chicken price was reported in Mhondoro-Ngezi (ZWL$433) followed by Chegutu, Kariba, Zvimba and Sanyati (ZWL$402) • The lowest price was reported in Makonde (ZWL$301) • The provincial average price was ZWL$383 Income and Expenditure Current Most Important Sources of Income
• Cross border 0.3 The highest proportion of households Beer brewing 0.6 continue to rely on Casual labour as the Gifts 1.4 Fishing 3.1 most important source of income (22.8%), Other 0.7 followed by small scale mining/ mineral Gathering natural products for sale e.g. firewood 1.2 Government social transfers 0.5 sales (12.1%) and formal salary/ wages Own business 2.2 (11.8%). Pension 1.5 Skilled trade/artisan 2.2 •Food crop production/ sales and Cash crop production 5.7 Petty trade 3.8 remittance within were amongst the most Livestock production/sales 3.3 important sources of income for 9% and Remittances outside 1 Small scale mining/mineral sales 12.1 8.5% of the households respectively. Remittance within 8.5 Food crop production/sales 9 Formal salary/wages 11.8 Vegetables production/sales 7.9 Casual labour 22.8 0 5 10 15 20 25 30 Proportion of households (%) Average Household Monthly Income
140 120 120
100 85 80
60
INCOME (USD) INCOME 41 39 40
20
0 2017 2018 2019 2020
•The provincial average household monthly income was on a declining trend since the year 2017 (US$120) to US$39 in 2020 Average Household Monthly Income for June 2020
Monthly income (ZWL$) Monthly income (USD) 10000 100 9000 90 8000 80 7000 70 64 6000 60 57 5122 48 5000 4565 50 46
ZWL$ 3862 39
3703 $ USD 4000 3111 40 3000 30 22 26 25 1801 2102 1996 2000 20 1000 10 0 0
•Provincially, the average household income for the month of June was ZWL$3111 (USD39). •Mhondoro-Ngezi (ZWL$5122), had the highest average monthly income while Chegutu (ZWL$1801) had the lowest average monthly income. Average Household Monthly Expenditure for June 2020
5000 100 4500 90 4000 80 3500 70 2963 3000 2557 60
2500 2266 50 USD ZWL$ 37 2000 1723 40 32 1416 1267 28 1500 1023 30 21 886 18 16 1000 20 13 11 500 10 0 0
• The average household expenditure for the month of June was ZWL$1723 (USD21). • Mhondoro-Ngezi (ZWL$2963) reported the highest average monthly expenditure while Kariba (ZWL$886) had the lowest average monthly expenditure. Food Expenditure Proportion of Food Expenditure
100
90
80
70 64 64 60 51 52 50
40
30
20 Proportion of total expenditure (%) expenditure total of Proportion 10
0 2017 2018 2019 2020
• The proportion of food expenditure was on an upward trend from 51% in 2017 to 64% in 2019. •The proportion did not change from 2019 to 2020. Proportion of Food Expenditure by District
100 90 80 70 66 66 70 62 64 64 58 61 60 50 40 30 20 10 Proportion of Food Expenditure(%) Food of Proportion 0
• Chegutu had the highest proportion of food expenditure at 70% followed by Zvimba and Mhondoro-Ngezi at 66%. • Kariba had the least proportion of food expenditure at 58%. Average Household 6 Months Expenditure
5000 100 4500 90 4000 3577 80 3500 70 3000 60
2500 50 44
USD ZWL$ 2000 1735 1718 40 1267 1500 1077 30 22 21 1000 809 695 20 13 16 545 10 9 500 10 7 0 0
• Provincially, the average household expenditure for the period January 2020 to June 2020 was ZWL$1267 (USD16) • Makonde had the highest average expenditure of ZWL$3577 (USD44) while Kariba had the lowest average monthly expenditure of ZW$545 (USD7) over the six months period Average Household Six Months Expenditure
1600 1377 1400
1200
1000 832 800
ZWL$ 633 600
400 262 203 178 200 11 0 Education (ZWL$) Agriculture Business (ZWL$) Health (ZWL$) Taxes (ZWL$) Social (ZWL$) Other (ZWL$) (ZWL$)
• The average household expenditure over the six months period was highest for agriculture at ZWL$1377 followed by education (ZWL$633. Taxes had the lowest expenditure of ZWL$11. Water, Sanitation and Hygiene (WASH) Ladder for Drinking Water Services
Service Level Definition
Safely Managed Drinking water from an improved water source which is located on premises, available when needed and free of faecal and priority chemical contamination
Basic Drinking Water Drinking water from an improved source provided collection time is not more than 30 minutes for a round trip including queuing
Limited Drinking Water Drinking water from an improved source where collection time exceeds over 30 minutes for a round trip to collect water, including queuing
Unimproved Water Services Drinking water from an unprotected dug well or unprotected spring
No Service Drinking water collected directly from a river, dam, lake, pond, stream, canal or irrigation channel
Note: Drinking Water is defined as water used for drinking, cooking, food preparation and personal hygiene Drinking water services refers to the accessibility, availability and quality of the main source used by households for drinking, cooking, personal hygiene and other domestic uses ‘Improved’ sources are those that are potentially capable of delivering safe water by nature of their design and construction. Such sources include piped water, boreholes or tube wells, protected dug wells, protected springs, and rainwater. This category now includes packaged and delivered water, considering that both can potentially deliver safe water Unimproved sources include unprotected dug wells and unprotected springs Access to Improved Drinking Water
100 88.9 90.5 90 86.0 78.9 80 75.3 74.6 72.4 71.1 69.6 68.0 70.3 69.2 70 65.5 63.6 60 53.2 53.5 50 40 30 20 Proportion of Households (%) Households of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province 2019 2020
• Provincially, access to improved sources of drinking water increased from 69.2% in 2019 to 74.6% in 2020 • Sanyati district (90.5%) had the highest proportion of households who had access to improved sources of drinking water • Kariba district (53.5%) had the least proportion of households who had access to improved sources of drinking water Main Drinking Water Sources
100 3.5 0.5 8.0 8.2 6.1 9.1 9.1 9.7 90 5.1 24.1 32.5 10.7 11.7 80 24.0 21.1 15.7 26.8 7.6 70 9.0 15.5 18.6 60 20.0 14.7 50 15.7 40 78.2 71.6 30 63.3 63.6 59.1 48.0 52.1 20 37.1 Proportion of households (%) households of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Basic water services Limited water services Unimproved water services Surface water services
• Approximately 60% of households in the province had access to drinking water from protected sources where collection time was not more than 30 minutes for a round trip including queuing • Provincially, 15.5% had access to drinking water protected sources were collection time was more than 30 minutes for a round trip including queuing • A tenth of the households in the province were drinking surface water from sources such as dams and rivers • Kariba district (32.5%) had the highest proportion of households drinking surface water Main Drinking Water Sources
• Kariba district (32.5%) had the highest proportion of households drinking surface water while Sanyati (0.5%) had the least Treatment of Drinking Water from Main Source
50 45 40 35 30 25 20 15
10 7.0 Proportion of households (%) households of Proportion 6.0 5.2 5 3.2 1.0 1.5 0.5 1.5 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province
• The treatment of drinking water from the main sources was below 10% across all the districts in the province Distance Travelled to Main Drinking Water Source
100 12.1 12.9 11.7 17.5 18.9 17.3 90 25.8 22.8 80 27.6 28.4 34.0 18.9 70 30.3 60 28.8 38.5 35.4 50 40 60.3 62.2 30 58.8 54.3 48.4 52.4 20 38.9 44.0
Proportion of Households (%) Households of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Less than 500m More than 500m but less than 1 km 1km and above
• Half of the households in the province travelled less than half a kilometer to access water. • Approximately one in five households in the province travelled more than a kilometer to access water. • Hurungwe (25.8%) and Kariba (22.8%) districts had the highest proportion of households travelling more than a kilometer to fetch water. Time Spent Queueing to get Water
100 4.0 2.0 2.6 5.6 12.6 9.7 10.6 8.7 90 17.7 19.6 10.8 11.1 80 19.7 15.7 19.4 24.1 26.0 70 19.1 18.9 22.0 60 35.9 10.5 50 19.1 25.5 40 70.7 62.6 30 57.6 59.4 53.6 20 44.4 42.3 38.8
10 Proportion of Households (%) Households of Proportion 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Less than 15minutes (or within premises) 15- 30 minutes 30 minutes - 1 hour More than 1 hour
• Approximately 50% of the households within the province queue for less than 15minutes to get water. • Makonde district (19.6%) had the highest proportion of households queueing for more than one hour to get water whilst Hurungwe district (2%) had the least. • Chegutu district (70.7%) had the highest proportion of households queueing less than 15minutes to get water. Methods used to Treat Drinking Water
20.4 Boil Add bleach/chlorine [jik or water guard] 2.0 Strain it through cloth 2.0 2.0 Use a water filter (ceramic,sand,composite,etc) 6.1 Let it stand and settle 67.3 Add water treatment tablet
• The most common method used to treat drinking water was boiling with 67.3% of households practicing this method. • The methods least used to treat drinking water were straining, filtering and allowing the water to stand and settle. Fetching of Water from Main Source by Sex and Age Group
100 0.51.5 1.51.5 0.51.5 2.6 1.5 4.0 3.0 2.0 5.5 2.1 2.6 1.0 1.5 1.7 90 11.0 13.3 14.1 21.7 13.4 17.7 16.2 80 70 60 50 92.5 86.0 82.0 82.7 82.3 40 76.3 77.3 79.3 30 20 Proportion of Households (%) Households of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Adult woman [15 years and above] Adult man [15 years and above] Female child [under 15 years] Male child [under 15 years]
• Generally, across all the seven districts, fetching of water was mainly carried out by adult women • Kariba district (92.5%) had the highest proportion of households with adult women fetching water whilst Chegutu district (76.3%) had the least. Violence Whilst Fetching Water
50
40
30
20 12.4 9.5 9.0 8.0
10 6.3 6.9 Proportion of Households (%) Households of Proportion 1.0 2.0 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province
• Makonde district (12.4%) had the highest prevalence of violence at water fetching points whilst Chegutu district (1%) had the least. Ladder for Sanitation
Service level Definition
Safely Managed Use of improved facilities which are not shared with other households and where excreta are safely disposed in situ or transported and treated off-site
Basic Sanitation Facilities Use of improved facilities which are not shared with other households
Limited Sanitation Facilities Use of improved facilities shared between two or more households
Unimproved Sanitation Facilities Use of pit latrines without a slab or platform, hanging latrines or bucket latrines
Open Defecation Disposal of human faeces in fields, forests, bushes, open bodies of water, beaches and other open spaces or with solid waste
Note: Improved sanitation facilities: Facilities that ensure hygienic separation of human excreta from human contact. They include flush or pour flush toilet/latrine, Blair ventilated improved pit (BVIP), pit latrine with slab and upgradeable Blair latrine. Household Sanitation Services
100 90 26.0 27.2 80 38.0 37.0 37.0 43.7 47.2 45.7 70 16.5 16.9 60 0.03.5 15.0 0.5 12.0 50 3.5 22.1 20.5 18.6 17.6 40 14.0 3.0 0.5 30 57.0 11.1 59.5 47.5 20 33.0 35.4 33.7 31.2 25.6 Proportion of households (%) households of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Open defecation Unimproved Limited Basic
• Kariba district (57%) had the least proportion of households practicing open defecation. • Chegutu district (22.1%) had the highest proportion of households sharing sanitation facilities. Household Sanitation Services
• Kariba district (57%) had the highest proportion of households practicing open defecation whilst Zvimba district (25.6%) had the least. Ladder for household Hygiene Services
Service Level Definition
Basic Availability of a handwashing facility on premises with soap and water
Limited Availability of a handwashing facility on premises without soap and water
No Facility No handwashing facility on premises
Note: Handwashing facilities may be fixed or mobile and include a sink with tap water, buckets with taps, tippy-taps, and jugs or basins designated for handwashing. Soap includes bar soap, liquid soap, powder detergent, and soapy water but does not include ash, soil, sand or other handwashing agents. Availability of Hygiene Services
100 1.5 2.0 3.5 3.5 2.1 3.0 7.5 3.3 90 80 70 60 50 98.5 97.5 96.5 96.5 97.9 97.0 92.5 96.6 40 30
20 Proportion of households (%) households of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province No service Limited Basic
• Provincially, 96.6% of households had no hand washing facilities. • Zvimba district (7.5%) had the highest proportion of households with a hand washing facility that had soap and water. Availability of Hygiene Services
• Mhondoro-Ngezi and Makonde had the highest proportion of households without hand hygiene place that had soap and water. Handwashing Practices at Critical Times
Before handling food 73.4
After using the toilet 71.1
Before and after eating 60.3
Whenever i feel like my… 20.5
Regularly 19.1
After changing… 11.5
After assisting the sick 5.1
Never 0.9
Other 0.8
0 10 20 30 40 50 60 70 80 Proportion of Households(%)
• The most observed critical times for handwashing were before handling food (73.4%), after using the toilet (71.1%) and before eating food (60.3%) Access to Services and Infrastructure Access to Police Services by District 100 90 77.8 78.9 80 74.5 69 70 65.7
60 53.8 53 53.3 50 40 30
20 Proportion of Households(%) of Proportion 10 0
• Sixty Six percent of households in the province , reported that Police services were accessible within one hour of travel. Access to Victim Friendly Services
100 93.3 85.9 90 81.5 78 78.6 80 72.7 71 68.3 70 60 50 40 30 20
Proportion of Households(%) of Proportion 10 0
• Victim Friendly Units were available across all rural districts in the province (78.9%) Access to Sexual Violence Services
100 91.7 85.5 90 80.4 80.8 80 76.4 70 65.5 66.2 66 60 50 40 30 20
Proportion of Households(%) of Proportion 10 0
• Access to Information on Services for Physical and Sexual Violence was high across all districts Access to Information on Sexual and Physical Violence
100 90 83.4 86.4 80 75.3 72.9 71.1 70 66 60 60 54.3 50 40 30
20 Proportion of Households(%) of Proportion 10 0
• The greatest proportion of households (71.%)reported that they had access to information on Sexual and Physical Violence Sources of Information on services for physical and sexual violence
Friends Other Governement Health and househol Televisio NewspapeSocial Internet Extension Health promoter relative Other Radio d membern r media browsing Worker workers s s UN/NGOs Police specify
Chegutu 70.4 0 0 1.9 0.0 0 5.6 35.2 5.6 5.6 3.7 7.4 0.0
Hurungwe 88.4 0 0 0 1.4 0 0 23.2 24.6 5.8 0 24.6 2.9
Kariba 24.3 8.1 0 0 0 0 29.7 40.5 13.5 5.4 21.6 13.5 10.8
Makonde 75.0 9.4 3.1 0 0 0 3.1 31.3 0 15.6 0 0 3.1 Mhondoro- Ngezi 74.7 9.3 10.7 1.3 12.0 1.3 4.0 45.3 17.3 10.7 1.3 6.7 1.3
Sanyati 86.2 29.8 1.1 0 3.2 0 8.5 20.2 10.6 6.4 2.1 22.3 2.1
Zvimba 75.9 9.3 9.3 1.9 13.0 0 18.5 14.8 5.6 27.8 3.7 9.3 7.4
Province 70.7 9.4 3.4 0.7 4.2 0.2 9.9 30.1 11.0 11.0 4.6 12.0 4.0
• The main source of information on physical and sexual violence was radio (70.7%) followed by health workers (30.1%) and health workers (11%). Access to Animal Health Centres
100 90 80 70 60 50 40 29.5 30.8 30 21.7 19.4 19.3 17.8 20
20 12 Proportion of Households of Proportion 10 0
• The proportion of households with access to animal health centres was generally low (21.7%). • Sanyati (30.8%) and Makonde (29.5%)had the highest proportion of households with access to animal health centres. • Only 12% of households in Mhondoro-Ngezi had access to animal health centres. Satisfaction on Animal Health Service
100 3.1 9.1 5.9 8.8 6.5 90 16.7
80 44.4 70 59.1 64.7 60 61.8 78.1 67.4 91.7 50 66.7 40
30 55.6
Proportion of households (% households of Proportion 20 17.6 31.8 29.4 23.2 10 16.7 15.6 11.8 8.3 0 3.1 2.9 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Not satisfied at all Somewhat satisfied Satisfied N/a
• A greater proportion (67.4%) of households were satisfied by the animal health service they are receiving • Mhondoro-Ngezi (91.7%) had the highest proportion of satisfied households ISALS and Loans Sources of loans
Other Financial Institutions 4
ISAL/SACCO 4
NGOs 4
Government /Rural Credit Fund 8
Banks 17
Friend /Relative 29
Farmers Organization38 38
0 5 10 15 20 25 30 35 40 45 50 Proportion of Households
• Farmers organizations (38%) were the major sources of loans followed by friends/relatives at (29%) Types of Loans
100 90 80 70 60 54.2
50 41.7 41.7 40 29.2 30 20 Proportion of Households(%) of Proportion 10 0 0 Livestock Agrochemicals Cash Inputs/Fertilizers Inputs/seeds
• The greatest proportion of households (54%) received loans in the form of inputs/seeds. Household Members who received a loan in the past 12 months (May 2019 to April 2020)
10
8
6
4 3.5 3.6
2 2
2 1.7 Proportion of households (%) (%) households of Proportion 0.5 0.5 0 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province
• Across the whole province, only 1.7% of household had members who had received a loan in the past 12 months. Loan Primary Use
Agricutural Value Chain 40
Consumption 35
Other Income Generating Activities 15
Other 15
0 5 10 15 20 25 30 35 40 45 50 Proportion of Households
• The highest proportion of households (40%) who received loans used them in the agricultural value chain. Use of Share Out From ISAL Group
100 35.0 90 33.3 33.3 29.1 80 37.5 70 100.0 60 50 100.0 100.0 33.3 46.7 70.0 37.5 40 56.4 30 20
Proportion of households (%) households of Proportion 6.7 33.3 10 6.7 25.0 3.6 5.0 16.7 9.1 6.7 0 0.0 5.0 1.8 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Zvimba Sanyati Mash West
Buying construction materials Education Livestock purchase Food Household utensils Agricultural inputs and equipment Financing Income generating projects Health costs No share out yet received
• Provincially, 56% of the ISAL share out were used to purchase food, while 29% were used to purchase household utensils Household Dietary Diversity Score (HDDS)
• Household dietary diversity is the number of food groups consumed by a household with a given reference period, and is an important indicator of food security. A more diversified household diet is correlated with caloric and protein adequacy, percentage of protein from animal sources, and household income. The HDDS indicator provides a glimpse of a household’s ability to access food as well as its socioeconomic status based on the previous 24 hours. The following 12 food groups were used to calculate the HDDS indicator: A. Cereals B. Roots and tubers C. Vegetables D. Fruits E. Meat, poultry, offal F. Eggs G. Fish and seafood H. Pulses, legumes, nuts I. Milk and milk products J. Oil/fats K. Sugar/honey L. Miscellaneous. Each food group was assigned a score of 1 (if consumed) or 0 (if not consumed). The household score ranged from 0 to 12 and is equal to the total number of food groups consumed by the household. • Dietary diversity based on HDDS categorized into three categories,
Less than 3 Low Dietary Diversity
4 - 5 Moderate Dietary Diversity
Above 5 High Dietary Diversity Household Dietary Diversity Score
100 11.5 12.0 90 18.6 20.9 25.6 25.1 29.6 24.0 80 70 43.5 46.5 60 55.8 53.7 50 54.9 50.0 40 63.8 61.3 30 20 45.0 41.5 10 20.0 26.0 25.6 25.4 Percentage of Households (%) Households of Percentage 10.6 9.0 0
Low Medium Acceptable
• Majority (54%) of households in Mashonaland West had a medium household dietary diversity. • Dietary diversity of 1 in every 4 households in Mashonaland West province is low. • The districts with highest proportion of households with low dietary diversity are Hurungwe (45%) and Kariba (42%). • Mhondoro – Ngezi had the highest proportion of households consuming diversified diet (30%). Household Consumption of Protein, Vitamin A and iron rich foods
• Protein which plays a key role in growth, is crucial for the prevention of wasting as well as stunting which takes place largely within the first 1000 days. Vitamin A and Iron deficiencies are some of the major contributors of mortality and morbidities among children women in developing. Iron deficiency, contributes to anaemia mainly among pre-school children and women. Anaemia contributes to the reduced productivity and quality of life in adulthood. The major contributors of anaemia and Vitamin A deficiency are low consumption of diet rich in micronutrients and macronutrients such as protein, Vitamin A and Iron. If tackled before the age of five, Vitamin A deficiency can reduce mortality and infectious diseases such as measles, diarrhoea and malaria up to a third.
• Protein rich foods include Pulses, Dairy, Flesh meat, Organ meat, Fish and Eggs. Vitamin A rich foods include Dairy, Organ meat, Eggs, Orange veg, Green vegetables and Orange fruits while iron rich foods include Flesh meat, Organ meat, and Fish. Household Consumption of Iron Rich Foods
100 90 80 70 60 50 40 33.5 32.5 30 23.6 21.6 22.3
Percentage of Households (%) Households of Percentage 17.6 20 14.0 13.6 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province
• Less than a quarter of households in Mashonaland West province (22%) consume iron rich foods. • Hurungwe and Zvimba had the lowest proportion of households consuming iron rich foods at 14%, while Kariba(34%) and Sanyati (33%) had the highest proportion. Number of days Iron Rich Foods Consumed
100 3.5 3.1 5.5 8.5 5.0 6.0 90 18.5 16.5 80 23.6 42.2 42.6 32.2 41.0 31.7 70 22.0 60 50 40 81.5 70.9 61.5 62.3 30 54.3 54.4 59.3 54.0 20
10 Proportion of Households (%) (%) Households of Proportion 0 Chegutu Hurungwe Kariba Makonde Zvimba Mhondoro-Ngezi Sanyati Mash West Never Consumed Consumed 1 to 6 days Consumed for 7 days
• Majority (62%) of households in Mashonaland West never consumed iron rich foods with 32% consuming for 1 to 6 days and 6% consuming daily. • Hurungwe(82%) had the highest percentage of households who never consumed any iron rich foods while Chegutu, Sanyati and Makonde had lowest at 54% . • Chegutu, Sanyati and Makonde had the highest proportion of households consuming iron rich foods for 1-6 days. • Kariba district (17%) had the highest proportion of households consuming iron rich foods on daily basis. Household Consumption of Protein Rich Foods
100 90 80 70 58.5 58.5 60 51.8 50 41.7 42.2 45.4 37.5 40 27.6 30 20
Proportion of Households(%) of Proportion 10 0
• Less than half of the households(45.4%) in Mashonaland West province consumed protein rich foods. • A total of 4 out of the 7 districts in the province had less than half of the households consuming protein rich foods. • Zvimba district had the least proportion with less than a third (27.6%) of households consuming protein rich foods. • Sanyati, Kariba and Makonde had the highest with more than half of the households consuming protein rich foods. Number of days households consumed protein rich foods
100 6.0 10.6 90 15.6 12.8 18.1 14.0 15.4 30.5 80 37.0 70 36.4 60 46.7 49.7 61.0 44.2 58.0 50 40.5 40 30 57.0 53.0 20 37.7 38.0 34.7 29.0 28.0
10 26.2 Proportion of Households (%) Households of Proportion 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Never Consumed Consumed 1 to 6 days Consumed for 7 days
• Less than a fifth of the households in Mashonaland West province consumed protein rich foods for 7 days with majority consuming protein rich foods for 1 to 6 days (46.7%). • Over a third (38%) of the households never consumed any protein rich foods in Mashonaland West province. • Hurungwe (57%) and Zvimba (53%) had the highest proportion of households that never consumed protein rich foods. • Kariba had the highest proportion of households that consumed protein rich foods on daily basis while Makonde had the highest proportion of those that consumed for 1-6 days. Household Consumption of Vitamin A Rich Foods
100 97.0 96.0 92.5 91.3 90.4 90 87.0 87.5 81.5 80 70 60 50 40 30
Proportion of Households (%) (%) Households of Proportion 20 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Mash West
• Majority of the households(90.4%) in Mashonaland West province consumed Vitamin A rich foods. • Mhondoro Ngezi (97%) had the highest proportion of households consuming Vitamin A rich foods while Kariba had the lowest (82%). Number of days Vitamin A Rich Foods Consumed
100 90 80 70 72.5 67.7 60 78.0 74.0 79.8 84.4 86.9 50 95.0 40 30 20 10.0 20.0 29.2 22.0 Percentage of Households (%) (%) Households of Percentage 10 15.9 13.6 12.1 12.0 7.5 0 2.0 3.1 1.0 4.0 5.0 4.2 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province
Never Consumed Consumed 1 to 6 days Consumed for 7 days
• Majority (79.8%) of households in Mashonaland West consumed Vitamin A rich foods on daily basis with 16% consuming for 1 to 6 days and 4% consuming daily. • Hurungwe had the highest proportion of households who never consumed Vitamin A rich foods. • Makonde (67.7%) had the lowest proportion of households consuming Vitamin A rich foods on daily basis while Zvimba had the highest at 95%. Minimum Dietary Diversity for Women (MDDW)
• Women of reproductive age (WRA) are often nutritionally vulnerable because of the physiological demands of pregnancy and lactation. MDD-W is a indicator of whether or not women 15–49 years of age have consumed at least five out of ten defined food groups the previous day or night.
• The ten food groups are: 1. Grains, white roots and tubers, and plantains 2. Pulses (beans, peas and lentils) 3. Nuts and seeds 4. Dairy 5. Meat, poultry and fish 6. Eggs 7. Dark green leafy vegetables 8. Other vitamin A-rich fruits and vegetables 9. Other vegetables 10. Other fruits. The proportion of women 15–49 years of age who reach this minimum in a population is used as a proxy indicator for higher micronutrient adequacy, one important dimension of diet quality. Women Meeting Minimum Dietary Diversity for Women 100 90 80 70 60 50 40 32.9 30 23.8 18.0 17.8 18.0 19.3 20.7 20 16.1 Proportion of Women(%) of Proportion 10 0
• Only 1 in 5 women of child bearing age in Mashonaland West meet the recommended minimum dietary diversity for women of at least 5 food groups per day. • Kariba (16.1%) had the lowest proportion of women meeting the recommended minimum dietary diversity while Sanyati (33%) had the highest proportion. Consumption of Iron, Vitamin A and Protein Rich Foods by Women(15-49yrs)
96.3 96.0 100 94.6 91.8 92.3 91.0 88.2 88.3 90 80 70 58.2 60 45.0 46.0 50 42.1 44.6 41.8 42.4 40 32.9 25.6 26.1 28.0 27.3 26.0
30 22.4 24.2 Proportion of women (%) (%) women of Proportion 20 14.0 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Iron rich Vitamin A Rich Protein rich
• A high proportion of women of child bearing age in Mashonaland West (92.3%) consumed vitamin A rich foods. Kariba and Hurungwe (88%) had the lowest proportion of women consuming Vitamin A rich foods while Zvimba and Mhondoro-Ngezi had the highest (96.3%) • The proportion of women who consumed iron rich and protein rich foods in Mashonaland West was low at 42.1% and 25.6% respectively • Zvimba had the lowest proportion of women consuming iron rich foods (14%) and protein rich foods(27.3%). • Sanyati had the highest proportion of women who consumed protein rich foods (42%) and iron rich foods (42%). Infant and Young Child Feeding Practices Infant and Young Child Feeding
• Infant and young child feeding is a key area to improve child survival and promote healthy growth and development. The first 2 years of a child’s life are particularly important, as optimal nutrition during this period lowers morbidity and mortality, reduces the risk of chronic disease, and fosters better development overall. beyond. • The indicators for assessing feeding practices in children 6–23 months of age include minimum dietary diversity (MDD), minimum meal frequency (MMF), minimum acceptable diet (MAD) among others.
• Minimum dietary diversity: Proportion of children 6–23 months of age who receive foods from 4 or more food groups. The 7 foods groups used for this indicator are: — grains, roots and tubers — legumes and nuts — dairy products (milk, yogurt, cheese) — flesh foods (meat, fish, poultry and liver/organ meats) — eggs — vitamin-A rich fruits and vegetables — other fruits and vegetables
• Minimum meal frequency: Proportion of breastfed and non-breastfed children 6– 23 months of age who receive solid, semi-solid, or soft foods (but also including milk feeds for non-breastfed children) the minimum number of times or more. Minimum number of times refers to:— 2 times for breastfed infants 6–8 months, — 3 times for breastfed children 9–23 months and — 4 times for non-breastfed children 6–23 months • Minimum acceptable diet: Proportion of children 6–23 months of age who receive a minimum acceptable diet (apart from breast milk). Infant and Young Child Feeding Practices
100 90 80
70 23 months (%) months 23 - 60 50 40 32.1 25.7 30 23.1 21.4 21.2 20.0 20.0 20.1 17.1 20 15.4 11.1 13.0 10 7.1 6.1 7.1 7.1 Proportion of Children 6 Children of Proportion 3.0 3.6 2.9 2.8 0.0 0.0 0.0 2.1 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Minimum Meal Frequency Minimum Dietary Diversity Minimum Accepatble Diet
• The proportion of children who received Minimum Meal Frequency in Mashonaland West province, was 20% with 13% receiving a minimum dietary diversity and 2% receiving Minimum Acceptable diet. • Chegutu had the highest proportion of children who received minimum meal frequency and minimum acceptable diet. Vitamin A Supplementation in Children 6-59 months of age
• World Health Organisation recommends vitamin A supplementation every 6 months to children 6–59 months of age in settings where vitamin A deficiency is a public health problem. Vitamin A supplementation is known to reduce all-cause mortality and the incidence of diarrhoea and measles in children aged six months to five years. The Vitamin A Supplementation scheme is as below:
Vitamin A supplementation scheme for infants children 6–59 months of age
Target group Infants 6–11 months of age Children 12–59 months of age
Dose 100 000 IU (30 mg RE) vitamin A 200 000 IU (60 mg RE) vitamin A
Frequency Once Every 6 months Vitamin A Supplementation in Children 6-59 months of age
100 90 80
59 months months 59 70 64.6 - 60 51.8 46.4 49.1 50 43.2 37.7 40 34.0 30 24.6 20
Proportion of Children 6 Children of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Mash West
• In Mashonaland West province, 43.2 % of children 6-59 months received age appropriate Vitamin A Supplementation doses. • Chegutu had the highest proportion of children who received the age appropriate Vitamin A supplementation at 64.6% while Mhondoro – Ngezi had the lowest at 24.5%. Illness in Children 0-59months
100 90 80 70 60 50 40 30 21.3
Proportion of Children (%) Children of Proportion 20 10.7 13.2 10 0 Diarrhoea Cough Fever
• A fifth of the children less than 5 years of age in Mashonaland West had cough while 13.2% had fever and 10.7% had diarrhoea. Child Nutritional Status Acute Malnutrition in Children 6-59 months of age
• Acute malnutrition is a form of under-nutrition caused by a decrease in food consumption and/or illness that results in sudden weight loss or oedema (fluid retention). Acute malnutrition can be moderate or severe, and prolonged malnutrition can cause stunted growth, otherwise known as stunting. • Moderate acute malnutrition (MAM), refers to weight-for-height z- score (WHZ) between −2 and −3 or mid-upper arm circumference (MUAC) between 115 millimeters and <125 millimetres. • Severe acute malnutrition (SAM), refers to WHZ < −3 or MUAC < 115 millimeters, or the presence of bilateral pitting edema, or both. • Global acute malnutrition (GAM) refers to MAM and SAM together; it is used as a measurement of nutritional status at a population level and as an indicator of the severity of an emergency situation . • Treatment of acute malnutrition includes a combination of community- based management and therapeutic foods/Ready-to-use therapeutic foods (RUTFs). Acute Malnutrition in Children 6-59 months of age 10
8 7.4 59 months (%) (%) months 59 - 6 3.7 3.6 4 3.0 3.1 2.6 2.4 1.7 2.7 2 1.0 3.7 2.0 2.1 2.6 2.4 1.7 1.0 0.9 1.0 1.1
0 Proportion of Children 6 Children of Proportion Chegutu Hurungwe Kariba Makonde Zvimba Mhondoro-Ngezi Sanyati Province MAM SAM
• Among the children screened for acute malnutrition using a MUAC tape in Mashonaland West province, 2.1% had Severe Acute Malnutrition (SAM) requiring admission into CMAM and 1.1 % had Moderate Acute Malnutrition (MAM) requiring Supplementary feeding. • Zvimba had the highest proportion of children identified with both Severe Acute Malnutrition and Moderate Acute Malnutrition at 3.7%. • Chegutu had the least proportion of Children with Acute Malnutrition (1%) Gender Based Violence Spousal and Other Forms of Gender Based Violence
50 45 40 35 30 25 20 0 15 0.6 10 19.5 0.3 0.5 0.5 0 Proportion of Households of Proportion 5 0.7 0 13.7 6.1 6.6 6.8 8.1 7.6 9.6 0
Spousal Violence Other Forms
• More respondents reported having experienced spousal violence (9.6%), than other forms of Gender Based Violence (0.3%) in the Province. • Spousal violence was highest in Zvimba District (19.5%) Forms of Gender Based Violence
Try to choke you or burn you on purpose 2.6 Threaten or attack you with a knife, gun, or other weapon 4.3 Force you with threats or in any other way to perform sexual… 1.7 Physically force you to perform any other sexual acts you did not… 3.4 Twist your arm or pull your hair 18.1 Physically force you to have sexual intercourse with him when… 12.9 Punch you with his fist or with something that could hurt you 19.8 Kick you, drag you, or beat you up 19.8 Deprive you of money to buy basic commodities for you or your… 37.9 Slap you 35.3 Push you, shake you, or throw something at you 47.4 Verbally abuse you, deprive you from physical needs in order to… 72.4 0 20 40 60 80 100 Proportion of Respondents(%)
• The main form of gender based violence reported was verbal abuse ,deprivation of physical needs(72%) followed by pushing or shaking (47%). Households Seeking Medical Attention as a Result of Gender Based Violence
50 45 40 37 35 30 25 20 15 10 7
Proportion of Households(%) of Proportion 5 3 0 0 0 0 0 0
• The proportion of households seeking medical attention as a result of gender based violence was low (3%) Households Livelihood Coping Strategies Households Livelihoods Coping Strategies
Category Coping Strategies
Stress • Borrowing money, spending savings, selling assets and selling more livestock than usual.
Crisis • Selling productive assets directly reducing future productivity, including human capital formation. • Withdrawing children from school • Reducing non food expenditure.
Emergency • Selling of one’s land thus affecting future productivity, more difficult to reverse /dramatic in nature. • Begging of food. • Selling the last breeding stock to buy food. Households Maximum Coping Strategy
100 1.5 11.0 10.8 6.0 11 90 16.6 15.5 5.0 15.5 12.6 7.5 8.2 9.5 13 80 22.6 9.5 17.6 10.0 10.3 70 30.0 8.5 12
60 16.6 50 5.5 40 71.5 70.8 76.4 30 66.3 66.5 64 49.2 49.0
20 Proportion of Households (%) Households of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province HH not adopting copying strategies stress crisis emergency
• Zvimba district (76.4%) had the highest proportion of households not adopting any copying strategy. • Kariba (51%) had the highest proportion of households adopting copying strategies with 15.5% of the households under emergency Corona Virus Disease 19 (COVID -19) Households Affected by COVID-19
100 90 80 70 60 50 42 40 30 24 18 19 21 20 15 17
Proportion of households(%) of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba
• Chegutu had the highest proportion of households (42%) that were affected by COVID-19. Awareness of COVID-19
100 98 100 100 98 99 99 99 99 90 80 70 60 50 40 30 20 10 Proportion of Households(%) of Proportion 0
• Majority of households in all districts over (98%) indicated that they had heard about COVID-19. Early Warning Information Sources
Neighbours/Friend Government s/Other Print media Social Internet Extension Radio Households Television (Newspapers media browsing Workers UN/NGOs Other District % % % % % % % % % Chegutu 92 2 2 0 2 2 23 0 0 Hurungwe 87 7 1 4 4 0 12 0 2 Kariba 76 8 0 0 6 0 42 16 1 Makonde 91 51 4 0 1 0 14 0 0
Mhondoro-Ngezi 56 17 7 2 5 3 68 5 0 Sanyati 82 41 9 4 2 1 35 1 3 Zvimba 50 0 4 4 0 0 92 0 0 Province 80 22 4 2 3 1 34 4 1
• The majority of households in the Province (80%) had heard about COVID-19 through the radio followed by Government Extension Workers at 34%. • In Zvimba (92%) of the households indicated that they got the information about COVID-19 from Government Extension Workers. Knowledge of how Covid19 is Spread
100 92 94 90 88 86 87 86 78 80 77 70 60 50 40 30
20 Proportion of Households (%) Households of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Zvimba Mhondoro-Ngezi Sanyati Province
• Zvimba had the highest proportion of households that indicated knowledge of how COVID-19 is spread at 94%. • Sanyati (23%) had the highest proportion of households that did not know how COVID-19 is spread. Knowledge of Toll –Free Number
100 90 80 70 60 50 38 40 34 36 30 27 26 22 19 20 Proportion of Households (%) Households of Proportion 10 10 0 Chegutu Hurungwe Kariba Makonde Zvimba Mhondoro-Ngezi Sanyati Province
• In Kariba (10%) of the sampled households indicated that they knew the Toll-Free number for COVID-19. • In the whole province (24%) of the sampled households knew the Toll-Free number for COVID-19. • Generally knowledge of COVID-19 Toll Free number was very low across all districts. Sources of Personal Protective Equipment (PPE)
100 90 81 80 76 68 69 68 70 63 58 60 53 52 50 45 43 41 44 41 40 34 30 30 26
20 13 12 Proportion of Households (%) Households of Proportion 8 9 10 8 10 5 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Province Purchases Homemade Donations
• A greater proportion of households across all districts were buying PPE. • The greatest proportion of households purchasing PPE was recorded in Hurungwe 81%. • Across the whole province (41%) of the sampled households were using home made PPE. • Only ( 12%) of the sampled households in the province had received PPE through donations. Affordability of Personal Protective Equipment 50 45 40 35 30 25 20 14 15 12 10 9 10 7 8 8
5 3 Proportion of Households (%) Households of Proportion 0
• PPE was not affordable in the province, 9% of the sampled households in the province indicated that the PPE was affordable. • Zvimba recorded the least proportion of households that could afford PPE (3%). COVID-19 Symptoms
Sudden loss Shortness of Runny or Muscle or Fatigue(tired of taste and Fever Cough breath Sore throat stuffy nose body aches Headaches ness smell District % % % % % % % % % Chegutu 67 82 31 36 22 10 48 28 1 Hurungwe 71 83 42 42 16 6 39 25 1 Kariba 78 85 45 44 45 28 29 28 6 Makonde 77 89 22 36 25 18 49 15 0 Mhondoro-Ngezi 70 87 24 52 27 16 71 36 7 Sanyati 74 76 48 41 39 21 38 27 3 Zvimba 72 77 37 42 14 8 42 35 1 Province 73 83 35 42 26 15 45 28 3
• The majority of households in the Province (83%) indicated cough as the major symptom of COVID- 19. • Generally respondents were aware of the COVID -19 symptoms. Household knowledge on how COVID-19 is Spreads
Being in close Touching a contact with Not covering your contaminated someone COVID-19 mouth and nose Not washing hand surface and including hand Coughing and sneezing without with a mask when with clean water and then touching shaking and hugging covering your mouth and nose in public soap your face Other District % % % % % % Chegutu 65 59 51 50 8 0 Hurungwe 66 60 54 49 29 1 Kariba 75 82 64 55 48 3 Makonde 55 65 49 42 7 1
Mhondoro-Ngezi 68 66 66 59 23 1 Sanyati 82 69 58 52 28 0 Zvimba 72 64 55 42 12 4 Province 69 66 57 50 22 1
• A greater proportion of households( 69%) indicated that corona spreads when people are in close contact with someone having the virus including shaking of hands and hugging. • Sixty- Six percent of households knew that coughing and sneezing without covering your mouth and nose is another way how COVID-19 spreads . Action taken when one Suspects Corona Infection
Stay at home and notify the nearest Consult local Go to the clinic health service traditional Call the toll free Home-based right away provider healer/prophet number remedies Dont know Districts % % % % % % Chegutu 58 22 1 20 2 12 Hurungwe 54 34 4 13 3 8 Kariba 55 52 2 3 3 3 Makonde 63 26 3 20 4 6 Mhondoro-Ngezi 88 21 0 6 7 2 Sanyati 70 25 5 11 2 7 Zvimba 66 35 2 15 2 5 Province 65 31 2 12 3 6
• The greatest proportion of households in the province (65%) indicated that when one suspects COVID-19 infection he/she should go to the clinic right away. • Kariba had the highest proportion of households (52% )that indicated that one should stay at home and notify the nearest health service provider. Disruption of Services
100 90 80 70 59 60 53 52 48 50 44 40 40 37 30 20
20 Proportion of Households of Proportion 10 0
YES
• Sanyati district recorded the least proportion of households (20%) that indicated disruption of services by COVID-19. • As a province, 44%of the sampled households reported that services were disrupted by the pandemic. Difficulties in Accessing Services Due to Covid19 (Food, Medical Supplies, Sanitary Products and Health Services)
100 90 90 80 73 69 70 66 59 59 61 59 55 57 60 53 51 52 53 48 51 48 49 50 46 45 37 38 40 40 35 33 30 20 20 20 14 10
Proportion of households % households of Proportion 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba food supplies Medical supplies sanitary Products Health services
• Households had difficulties in accessing basic services due to COVID-19. • In Kariba 90% of the sampled households had difficulties in accessing food supplies. • The greatest proportion of households that had difficulties in accessing medical supplies was reported in in Makonde (69%). • Makonde had the greatest proportion of households who had difficulties in accessing sanitary products( 53%). Difficulties in Accessing Services Due to Covid19 (water, transport, agricultural extension and Security Services)
100 90 77 79 78 79 80 75 70 62 65 64 60 48 49 50 43 40 29 31 30 23 24 26 25 23 19 17 17 20 14 7 8 7 10 6 3 5
0 Proportion of Households (%) Households of Proportion
Water Public transport Agric Extension Security
• The greatest proportion of household that had difficulties in accessing public transport due to COVID-19 was recorded in Makonde and Hurungwe (79%) followed by Kariba (78%). • Chegutu had the greatest proportion of households (62%) who had difficulties in accessing agricultural extension due to COVID-19. Effects of COVID-19 on Household Income
Failed to Gender- Restricted Loss of access Failed to Reduced based access to business Loss of health access basic sources of Reduced Reduced violance agricultural income employment facility commodities income salaries food sources (GBV) markets Districts % % % % % % % % % Chegutu 5 2 2 22 83 2 39 0 4 Hurungwe 15 2 2 5 50 1 14 1 37 Kariba 38 5 1 11 31 0 52 1 5 Makonde 17 5 7 5 57 4 13 0 19
Mhondoro -Ngezi 21 4 2 18 70 3 44 0 6 Sanyati 18 14 8 32 40 1 24 0 10 Zvimba 14 10 1 14 50 9 25 0 17 Province 18 6 3 15 55 3 31 0 14
• The greatest proportion of households in the Province( 55%) cited the major effect of COVID-19 as reduced source of income. • Chegutu had the highest proportion of households at 83% followed by mhondoro-Ngezi and Makonde at 70% and 57% respectively that indicated reduced income as the major effect of COVID-19 Shocks and Hazards Households that Reported Different Shocks
Cash shortages 69 Drought 57 Prolonged mid-season dry spell 56 Cereal price changes i.e. sharp drop or increase 56 Crop pests 42 Livestock price changes i.e sharp drop or increase 28 COVID-19 Pandemic 22 Livestock diseases 18 Livestock deaths 17 Human wildlife conflict 14 Other health related (eg TB, BP) 5 HIV and AIDS illness 5 Loss of employment by key household member 4 Malaria diseases incidents 4 GBV ( physical or sexual violence within the home) 2 0 10 20 30 40 50 60 70 80 90 100 Proportion of Households (%)
• Cash shortage (69%), Drought (57%), Prolonged dry spells (56%) and cereal price changes (56%) were reported as major shocks in the province. Households Affected by COVID-19
100 90 80 70 60
50 42 40 30 24 19 21
20 15 18 17 Proportion of households(%) of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba
• Chegutu had the highest proportion of households (42%) that were affected by COVID-19. Severity of COVID -19 in Households 100 90 90 85 81 79 80
70 62 60 50 43 43 40 34 37 30 24 20 14 13 15
Proportion of households(%) of Proportion 12 7 7 10 10 4 6 0 2 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Minor/Mild Moderate Severe
• Generally the impact of Covid -19 was severe across all districts. • Zvimba (90%) had the greatest proportion of households that indicated that the impact of COVID-19 was severe. Households Affected by Change in Cereal Prices
100 90 82 80 73 69 70 61 60 50 45 40 38 30 26
20 Proportion of households (%) households of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba
• The greatest proportion of households affected by cereal price increase was recorded in Kariba (82%). • Mhondoro- Ngezi reported the least proportion of households affected by cereal price increase (26%). Severity of Changes In Cereal Prices
100 93 94 98 88 90 80 80 73 70 67 60 50 40 28 30 25 20
Proportion of households (%) households of Proportion 20 9 10 7 5 5 1 2 1 1 3 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Minor/Mild Moderate Severe
• The impact of cereal price changes was severe across all districts with Sanyati recording the highest proportion of households that were severely impacted (98%) followed by Kariba (94%). Households affected by Cash Shortages
100 92 92 90 85 80 70 65 65 59 60 50 40 30 30 20
10 Proportion of households (%) households of Proportion 0
• A greater proportion of households (92%)who were affected by cash shortages were recorded in Chegutu and Kariba. • Mhondoro –Ngezi had the least proportion of households affected by cash shortages(30%). Severity of Cash Shortages in Households
100 96 91 92 92 90 79 80 74 70 64 60 50 40 29 30 24
20 17 Proportion of households (%) households of Proportion 8 10 7 7 8 1 2 1 3 2 3 1 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba Minor/Mild Moderate Severe
• Sanyati was severely impacted by cash shortages (96%), followed by Zvimba and Kariba at 92%. • The impact of cash shortages was severe across all districts. Household affected by Prolonged Dry Spell
100 90 79 80 70 68
60 55 53 54 50 44 41 40 30
20 Proportion of households (%) households of Proportion 10 0 Chegutu Hurungwe Kariba Makonde Mhondoro-Ngezi Sanyati Zvimba
• Chegutu had (79%) of its sampled households affected by prolonged mid-season dry spell. • Kariba was least affected by the dry spell at (41%). Severity of Prolonged Dry Spell in Households 95 96 100 91 94 90 85 83 85 80 70 60 50 50 46 40 30 20 13 13 14 9 6 Proportion of Households(%) of Proportion 10 5 5 0 0 2 0 1 2 3 2 0
Minor/Mild Moderate Severe
• A greater proportion of households in Sanyati and Mhondoro-Ngezi were severely impacted by prolonged mid-season dry spells, (96%) and (95%) respectively. Coping with shocks and Hazards
Dry Spells 80 18 1
Covid19 48 44 7
Cereal Price Changes 80 20 1
Cash Shortage 72 26 2
0 10 20 30 40 50 60 70 80 90 100 Proportion of Households (%)
Unable to cope Able to cope with difficulty Able to cope without difficulty
• In Mashonaland West Province generally, households were unable to cope with shocks and hazards. • For COVID-19, only 7% of the sampled households were able to cope without difficulty. Recovery from shocks
Cash shortages 34.3 46.7 17.9 1.1
Cereal Prices 36.7 48.1 14.6 0.6
Dry Spells 34.8 42.6 21.9 0.6
Covid 18.1 60.6 20.6 0.6
0 10 20 30 40 50 60 70 80 90 100 Proportion of households (%)
Did not recover Recovered some, but worse off than before [event] Recovered to same level as before [event] Recovered and better off
• Generally the greatest proportion of sampled households in the province recovered from the shocks experienced but were worse off than before the event. • Of the households that were affected by Covid19 , 60.1% reported that they recovered but were worse off than before the event. Food Security Food Security Dimensions
Figure 1: Dimensions of Food Security (Jones et al; 2013) Food Security Analytical Framework
• Food security exists when all people at all times, have physical, social and economic access to food which is safe and consumed in sufficient quantity and quality to meet their dietary needs and food preferences and it is supported by an environment of adequate sanitation, health services and care allowing for a healthy and active life (Food and Nutrition Security Policy, 2012).
• The four dimensions of food security as give in Figure 3 are:
• Availability of food • Access to food • The safe and healthy utilization of food • The stability of food availability, access and utilization Food Security Analytical Framework
• Each of the surveyed households’ potential to acquire minimum expenditure food basket (Figure 3) was computed by estimating the household's likely disposable income (both cash and non cash) in the 2019/20 consumption year from the following possible income sources; • Cereal stocks from the previous season; • Own food crop production from the 2019/20 agricultural season; • Potential income from own cash crop production; • Potential income from livestock ; • Potential income from casual labour and remittances; and • Income from other sources such as this, pensions, gardening, formal and informal employment Food Security Analytical Framework
• Household Cereal Security Status
• From the total minimum expenditure food basket, the total energy that could be acquired by the household from the cheapest available sources using its potential disposable income was also extracted and compared to the household’s minimum energy requirements.
• When the potential energy a household could acquire was greater than its minimum energy requirements, the household was deemed to be food secure. When the converse was true, the household was defined as food insecure.
• The severity of household food insecurity was computed by the margin with which its potential energy access is below its minimum energy requirements. Summary of Food Security Status Findings
• During the peak hunger period (January to March 2021) it is estimated that approximately 52.1%of the rural households in Mashonaland West will be cereal insecure. • The 52.1% of rural households will translate into approximately 659 640 individuals requiring 97 627MT of cereal (Maize Grain) Cereal Insecurity Progression by Income Source
100 96 99 100 93 86 87 86 90 81 81 81 80 74 70 64 62 57 60 51 52 50 40 29 30 20 11 10 Proportion of households (%) households of Proportion 0 Food insecurity from Food insecurity from Food insecurity from Food insecurity from Food insecurity from Food insecurity from cereals stocks cereals stocks plus foodcereals stocks plus foodcereals stocks plus foodcereals stocks plus foodcereals stocks plus food crops crops plus cash crops crops plus cash crops crops plus cash crops crops plus cash crops plus remittances plus livestocks plus plus livestocks plus casual labour and casual labour and remittances remittances plus income 2017/18 2018/19 2019/20
• Considering all incomes, the food insecurity prevalence is projected to be 52% during the peak hunger in the 2020/21 consumption year. • This has increased from 29% in the 2018/19 consumption year. Food Insecure Households
District Apr - Jun Jul - Sept Oct - Dec Jan - Mar
Chegutu 21.6 34.2 46.2 54.3
Hurungwe 29.0 40.5 48.5 56.5
Kariba 41.0 54.5 63.0 69.5
Makonde 6.2 15.4 23.6 35.4
Zvimba 26.1 44.7 56.3 63.3
Mhondoro-Ngezi 10.6 19.6 24.6 41.2
Sanyati 20.5 29.0 38.0 44.0
Province 22.2 34.1 43.0 52.1
• Kariba will have the greatest proportion of households (69%) that will be food insecure during the peak hunger period. • The least proportion of households (35.4%)that will be food insecure during the peak hunger period was recorded in Makonde. Food Insecure Population
Apr - Jun Jul - Sept Oct - Dec Jan - Mar
Chegutu 36,312 57,424 77,692 91,203
Hurungwe 104,411 145,815 174,618 203,421
Kariba 18,550 24,658 28,504 31,445
Makonde 10,334 25,835 39,613 59,419
Zvimba 75,168 128,652 161,900 182,137
Mhondoro-Ngezi 12,043 22,365 28,099 47,023
Sanyati 25,312 35,807 46,920 54,328
Province 281,143 431,268 544,090 659,640
• During the peak hunger period (January to March 2021) it is estimated that approximately 659 640 people in Mashonaland West will be cereal insecure. • Hurungwe will have the greatest number of food insecure people 203 421 during the peak hunger period. Cereal Requirements (MT) by District by Quarter
Apr - Jun Jul - Sept Oct - Dec Jan - Mar
Chegutu 5,374 8,499 11,498 13,498
Hurungwe 15,453 21,581 25,844 30,106
Kariba 2,745 3,649 4,219 4,654
Makonde 1,529 3,824 5,863 8,794
Zvimba 11,125 19,041 23,961 26,956
Mhondoro-Ngezi 1,782 3,310 4,159 6,959
Sanyati 3,746 5,299 6,944 8,041
Province 41,609 63,828 80,525 97,627
Hurungwe District has surpassed all other districts with regards to cereal requirements and would require 30 106 MT of cereal during the peak hunger period. Conclusions and Recommendations Conclusions and Recommendations
• Despite the pronouncement by Ministry of Primary and Secondary Education ,that no child should be denied the privilege of education because of non payment of fees ,the proportion of children that are being sent away from school due to non payment of fees continue to increase every year.
• The Ministry of Education should ensure that primary and secondary institutions of learning abide to the effected policy that prohibits the sending away of children from school because of non payment of fees.
• The Government(44%) continue to be the main source of social protection support in the Province.
• Provision of Resilience Programming support from all sources was low across all districts. In line with the global mode to strengthen community resilience, there is need for the Government of Zimbabwe and its partners to step up resilient building programming in rural districts.
• In recognition of the impact vulnerability attributes has on household’s food and nutrition security, the Government and its Development partners need to scale up interventions for the families who have orphaned children, physically/mentally challenged members and chronically ill members. Conclusions and Recommendations
• Gender Based Violence is still rampant, with spousal violence being the most common form of violence. It is worrisome that there is still under reporting of cases and lower proportions of survivors who seek help. The Ministry responsible for Gender social aspects need to increase community awareness on the negative effects of Gender Based Violence and importance of seeking help.
• There is also need to establish One Stop Centres and Shelters in all the Districts to enable survivors to seek assistance without facing further hindrances such as transport challenges.
• In view of spousal violence which was reportedly higher than other forms of Gender Based Violence, there is need to closely investigate, through research its drivers a household level.
• Share outs in ISALs were mostly used to purchase food, purchase household utensils and financing income generating projects, an indication that households are benefitting positively from this community initiative. In order to sustain the running of these community ISALS , further training in the establishment and management of ISALs which will ultimately lead to improved livelihoods and sustainable development is recommended. Conclusions and Recommendations
• The proportion of crops being attacked by the fall armyworm is on the increase since 2016/17 season. The majority of farmers are not taking control measures upon identification of the pest. Farmers who are taking control measures are finding their measures unsuccessful. There is need to come up with a robust program to deal with the pest through public private partnerships.
• Government and its development partners should engage on scaling up irrigation infrastructure in response to the climate change and its effects that include decrease in crop production.
• Cattle mortality rates have remained above acceptable rates. The deaths are mainly due to diseases and there is low access to animal health centers by farmers. There is need for Government and Development partners to capacitate the department of veterinary services with transport , dip chemicals and maintenance of infrastructure. The Government should establish private public partnerships that facilitate availability and production of affordable chemicals at community level.
• Open defecation was reported across all districts. This requires further in-depth investigations, including identification of social-cultural barriers to the uptake of optimum sanitation facilities and practices.
• Elimination of open defecation through availing of resources (both software and hardware) for the construction of latrines using locally available resources is recommended, and priority should be given to Kariba and Sanyati. Conclusions and Recommendations
• Using water from dams and rivers for drinking and cooking was noted in all the districts. The District Development Fund (DDF) should drill more boreholes especially in Hurungwe, Kariba, Makonde and Zvimba.
• Respondents were aware of covid-19 in all districts. They were also aware of covid19 symptoms and how the virus is spread. However PPE was not affordable to most households.
• Covid-19 disrupted a lot of services and paused difficulties in accessing basic services such as health, security and extension.
• Covid Taskforce Teams at all levels need to intensify awareness of covid-19 toll- free number.
• Households experienced different shocks and hazards and most household heads could not cope
• Climate proofing agriculture would go a long way in mitigating effects of climate change and variability.
• Rural food insecurity is estimated to reach 52% during the peak hunger period (January to march 2021). This is an increase from 29% last year. The food insecurity prevalence translates to 97 627MT maize grain. Food assistance programmes should be targeted to those households that have been found to be food insecure. Conclusions and Recommendations
• Majority of the households across the province did not consume a diverse diet and this is a cause of concern. At the same time the food consumption profiles for most of households varied from borderline to poor which might be an indication of food shortage in the affected households.
• The diets of most of the households lacked in iron. Most women of child bearing age failed to meet the minimum dietary diversity for women and also lacked in iron which exposed them to anaemia and iron deficiency. The percentage of children receiving Minimum Acceptable Diet remains low in the province and this is a cause for concern.
• The Food and Nutrition Committees across all the districts should identify the drivers of low dietary diversity and come up with innovative multisectoral intervention to improve the dietary diversity across the all the age groups. This should include diversified food production at household level. This could be initiated through the healthy harvest trainings.
• The high proportion of children who were identified with acute malnutrition through MUAC screening is a cause of concern in most districts in the province. There in need for Ministry of Health and Child Care to scale up active case finding for acute malnutrition across all the districts for an early detection and treatment of these children.
• The low coverage of vitamin A Supplementation in the province requires Ministry of Health and Child Care to scale up Vitamin A supplementation through the Village Health Workers particularly in districts such as Mhondoro Ngezi, Sanyati and Hurungwe. Writing Team
Provincial Team • Mugandani Media - Local Government and Public works • Chikomo Abigail - Ministry of Agriculture, Water and Rural Settlement • Chigumbu Walter - Ministry of Health and Child Care National Team: • Nester Gumbo - Ministry of Agriculture ,Water and Rural Settlement • Nyadzayo T Krispin- Ministry of Health and Child Care • Miriam Banda - Food and Nutrition Council • Innocent Mangwiro – Food and Nutrition Council