Lepr Rev (2017) 88, 533–542

The impact of seasonal climate on new case detection rate of leprosy in (2008–2012)

ALINE CRISTINA ARAU´ JO ALCAˆ NTARA ROCHA*, WASHINGTON LEITE JUNGER**, WESLEY JONATAR ALVES DA CRUZ* & ELIANE IGNOTTI* *University of the State of Mato Grosso - UNEMAT, Rua dos Tuiuiu´s, 660 Vila Mariana, Ca´ceres-MT-Brasil, CEP. 78200-000 **University of the State of Rio de Janeiro - UERJ, Institute of Social Medicine, Rio de Janeiro - RJ, Brasil

Accepted for publication 2 August 2017

Summary Objective: To examine the impact of climatic seasonality in the new case detection rate of leprosy in Brazil according to geographical regions, climates and biomes over a 5-year period, 2008–2012. Methods: We conducted an ecological study of the monthly new case detection rate of leprosy in spatial aggregation of Brazilian geographical regions, climates and biomes, applying a linear regression models with Poisson function to estimate seasonal rates using January as the reference month. Results: Monthly seasonal patterns of leprosy detection rates were recorded between different geographic regions, biomes and climates, with a predominance of increases in the autumn, in the months of March and May, and in winter in the month of August. Conclusions: The detection rate of leprosy in Brazil has a seasonal pattern with specific variations between geographical regions, climates, and biomes. The highest peaks in the detection rates were observed in May (autumn) and in August (winter). In addition to the supply and accessibility of healthcare services, these patterns, may also be related to cultural and environmental factors.

Keywords: Detection, Seasons, Environment

Introduction

Seasonal studies of the incidence of infectious diseases in areas of tropical and subtropical climates are frequent, particularly for dengue, malaria, influenza and measles among others.1–3 Environmental determinants are included among the main factors related to

Correspondence to: Aline Cristina Arau´jo Alcaˆntara Rocha, University of the State of Mato Grosso – UNEMAT, Rua dos Tuiuiu´s, 660 Vila Mariana, Ca´ceres-MT-Brasil, CEP. 78200-000 (e-mail: [email protected])

0305-7518/17/064053+10 $1.00 q Lepra 533 534 A.C.A.A. Rocha et al. seasonality, although the exact mechanism of transmission of these diseases is poorly understood. However, there are rare exceptions.4 Leprosy is a contagious, infectious disease, the transmission factors of which are mainly related to unfavourable living conditions and social inequalities. It has a high detection rate in Brazil, with 15·44 cases per 100,000 inhabitants in 2013. The territorial distribution is heterogeneous, with the most endemic areas being the North, Northeast and Midwest (http://www.who.int/lep/resources/Cluster_analyses/en/). The epidemiological distribution of the disease requires an understanding of many regional aspects. Brazil is a broadly diverse country in its politics, culture, economy and environment. It is organised into five geographical regions, five climates and six biomes.5 It is organised in five geographic regions classified in North, Northeast, Southeast, South and Midwest; and, presents five most important climates defined in Equatorial, Temperate, Central Tropical Brazil, Eastern Tropical Northeast, and Equatorial Tropical Zone. Other environmental and geographical classification refers to biomes. It means ‘a set of life’ (vegetal and animal) constituted by the grouping of contiguous and identifiable types of vegetation on a regional scale, with similar geoclimatic conditions and shared history of changes, resulting in a biological diversity of its own.5–7 The six biomes are ‘Amazon’, ‘’, ‘Pantanal’, ‘’, ‘Pampa’, and ‘’.6 This territorial classification (geographical region, climate and biomes) overlapping in some way, and they share similarities; however, there are important distinctions. With regard to geographical and environmental characteristics, the North region includes the Equatorial climate, a small part of the Equatorial Tropical Zone climate in the far north and the Amazon biome; the Northeast region includes the Eastern Tropical Northeast climate, the Equatorial Tropical Zone climate, and part of the Central Tropical Brazil climate, along with the ‘Cerrado’, ‘Caatinga’ and Atlantic Forest biomes; the Southeast Region includes the Central Tropical Brazil climate and ‘Cerrado’ and Atlantic Forest biomes; the South region includes the Central Tropical Brazil and Temperate climates and the ‘Pampa’ and Atlantic Forest biomes, and the Midwest region includes the Equatorial and Central Tropical Brazil climates along with the Amazon, ‘Pantanal’ and ‘Cerrado’ biomes.5,6 With such a diversity of climates and biomes, we can assume that endemic distribution analysis conducted only by geographical region cannot possibly account for all the many variations found in Brazil (Figure 1). It is recognised and understood that leprosy is not a seasonal disease and that efforts to diagnose and treat this disease should continue year-round. However, the relationship between leprosy and environmental factors has gained strength in recent years thanks to advancements in molecular biology.8 Thus, an analysis of leprosy detection as it pertains to the seasons may offer insights into public health resource allocation to better control the disease. This study aimed to examine the impact of climate seasonality on the new case detection rate of leprosy according to Brazilian geographical regions, climates, and biomes in a 5-year period (2008–2012).

Methods

We conducted an ecological analysis of the impact of climate seasonality on the detection rate of leprosy in Brazil for the 5 years between the beginning of 2008 and the end of 2012. We used the detection rate of new cases of leprosy as a proxy for the leprosy incidence rate. Seasonality of leprosy 535

Figure 1. Brazil - Geographical regions, climate and biomes. Source: IBGE.

New cases of leprosy reported per municipality in Brazil during the proposed period were obtained from the Notifiable Diseases Information System (SINAN). Population estimates for calculating rates were obtained from the Brazilian Institute of Geography and Statistics (IBGE). We aggregated the number of new cases of leprosy diagnosed by Brazilian municipalities in monthly totals by geographic region, climate, and biome. For municipalities with more than one biome or climate, we classified them according to the spatial location of the urban centre, where most of the population is concentrated, through the overlap of cartographic databases of IBGE climates and biomes using ArcGIS version 9.2 (ESRI, California, USA). The data were organised in spreadsheets by geographic region, climate, and biome, each containing the monthly aggregate number of new leprosy cases and the annual estimated population in the twelve months for years 2008 to 2012. To identify the climate seasonality in leprosy detection rate we used linear regression models with Poisson function for rates, using January as the reference month. The outcome variable was the number of new leprosy cases per month. The logarithm of the population for each spatial unit of geographical regions, climates, and biomes was included in the model as offset. The analyses were performed using R version 3.1.0 (R Foundation for Statistical 536 A.C.A.A. Rocha et al. Computing, Vienna, Austria) at 5% significance level. The regression coefficients estimates obtained from modelling were converted into monthly Relative Risks and calculated as monthly percentage variations in leprosy detection rates. For comparative analysis of the spatial distribution of the variation in the seasonal leprosy detection rate, we considered only the statistically significant results when preparing maps by geographic regions, climates, and biomes, using ArcGIS 9.2. To facilitate the presentation of maps, we selected the first month of every season of the year, that is, March for autumn, June for winter, September for spring, and December for summer. This study was conducted using secondary data from the Ministry of Health (MoH) and the IBGE. Since the data is in the public domain, we have received an official statement dismissing the mandatory submission to the research ethics committee.

Results

As shown in Table 1, the detection rate of leprosy in Brazil increased in the March and May (autumn) and August (winter), and decreased in the December (summer). In the analysis of seasonality by geographic regions, monthly seasonal patterns were similar in the North, Northeast, Southeast, and Midwest regions, which showed statistically significant variations in leprosy detection rates for almost every month of the year. The largest increases were observed in March and May (autumn) and August (winter) when compared to January as a reference and the largest decreases were observed in December (summer). The seasonal pattern for the South region was distinct from the other regions, with the largest increases in the October and November (spring), March to May (autumn) and August (winter) (Table 2). The seasonality on detection rate variations in the Equatorial and Tropical climates was similar in the North and South regions. Nevertheless, for the Semi-arid, Highland Tropical, and Subtropical climates, distinct variations were observed in the geographic regions where they are found (Figure 2).

Table 1. Seasonality analysis of the detection rate of leprosy according to the months of the year * in Brazil, 2008– 2012

Months b1 % variation CI (95%) P value

February 0·11 11·90 (09–14) ,0·001 March 0·19 20·90 (18–23) ,0·001 April 0·07 7·70 (05–10) ,0·001 May 0·15 16·60 (13–19) ,0·001 June 0·05 4·80 (02–7) ,0·001 July 0·07 7·70 (05–10) ,0·001 August 0·19 20·50 (17–23) ,0·001 September 0·08 8·50 (06–11) ,0·001 October 0·03 3·40 (01–05) 0·004 November 0·02 1·90 (201–04) 0·097 December 20·22 220·00 (222–(218)) ,0·001

Source: SINAN/SVS/MoH; IBGE. *January reference month. Seasonality of leprosy 537

Table 2. Seasonality analysis of the detection rate of leprosy according to months of the year* by geographic regions, Brazil, 2008–2012

NW NE SE S MW Regions/ months %var p %var p %var p %var p %var p

February 13·80 0·000 9·00 0·000 9·20 0·002 5·00 0·407 21·90 0·000 March 28·90 0·000 15·60 0·000 19·60 0·000 17·20 0·006 28·70 0·000 April 17·60 0·000 2·10 0·250 8·10 0·006 3·40 0·572 11·10 0·000 May 25·40 0·000 9·80 0·000 19·70 0·000 15·60 0·012 20·80 0·000 June 12·90 0·000 22·80 0·124 6·90 0·019 5·20 0·390 13·00 0·000 July 6·40 0·017 4·80 0·008 9·20 0·002 11·30 0·066 14·30 0·000 August 20·10 0·000 16·50 0·000 23·90 0·000 14·20 0·022 29·70 0·000 September 12·50 0·000 2·66 0·146 14·80 0·000 12·90 0·036 11·90 0·000 October 1·20 0·649 24·70 0·010 16·20 0·000 20·30 0·001 10·40 0·001 November 6·40 0·017 23·60 0·050 6·70 0·023 16·90 0·007 2·60 0·378 December 227·90 0·000 225·90 0·000 0·30 0·896 20·20 0·976 220·30 0·000

a) % variation: is derived from the relative risk obtained from exponential ß. b) NO: ‘North’, NE: ‘Northeast’, SE: ‘Southeast’, S: ‘South’, MW: ‘Mid-West’. Source: SINAN/SVS/MoH; IBGE. *January reference month.

There was also a pattern of higher increments in the variation of leprosy detection rates in the March and May (autumn) and August (winter) for most climates, except for the Tropical climate, which showed larger increases in the October and November (spring) and March and May (autumn). We found that in the Highland Tropical climate, the variation in the leprosy detection rate decreased in June (winter) and December (summer) (Table 3). Among the biomes, the largest increases in the detection rate of leprosy occurred in the March to May (autumn), August (winter) and November (spring). In December (summer), we observed decreases in the Amazon, Atlantic Forest, ‘Cerrado’ and ‘Caatinga’ biomes, which also showed decreases in June (winter) and October (spring). The variations in the of detection rate leprosy in the ‘Pampa’ and ‘Pantanal’ biomes were not statistically significant (Table 4). Figure 2 shows the spatial distribution of variations in the leprosy detection rate in March (autumn), June (winter), August (spring), and December (summer), during the five-year study period, by geographic region, climate, and biome. Only statistically significant variations are presented. We found that the climate seasonality in the March (autumn) showed increases in leprosy detection rates for all five geographic regions, all five climates, and three of the six biomes (‘Pampa’ and ‘Pantanal’ excluded). In June (winter), the increments in the variation of leprosy detection rates were observed in the North, Southeast, and Midwest regions, in the Equatorial and Central Tropical Brazil climates, and in the Amazon and ‘Cerrado’ biomes. Increases in the leprosy detection rate in the spring were observed in almost all geographic regions except the Northeast, which also showed seasonal variation for the Equatorial Tropical Zone climate and ‘Caatinga’ biome, inserted in this region. In December (summer), we observed that the North, Northeast and Midwest regions and the climates included among them, showed decreases in the variation of leprosy detection rates. Conversely, the Temperate climate and ‘Pampa’ biome in the South region and the ‘Pantanal’ biome in the Midwest region (Pantanal is the smallest biome of Brazil) showed no variation in the leprosy detection rates. 538 A.C.A.A. Rocha et al.

Figure 2. Distribution of seasonal variation in the detection rate of leprosy in Brazil by geographic region, climate, and biome according to the season: 2008–2012. *Statistically significant increases and decreases.

Discussion

This is the first study to analyse climate seasonality in the detection of leprosy, which is not traditionally viewed as a seasonal disease. These findings show monthly seasonal patterns in different detection rates of leprosy among geographic regions, climates, and biomes in Brazil, with the largest increases in detection found in autumn, particularly in March and May, and in Seasonality of leprosy 539

Table 3. Seasonality analysis of the detection rate of leprosy according to months of the year* by, climates, Brazil, 2008–2012

EQUA TEMP CTB ETN ETZ Climate/ Months %var p %var p %var p %var p %var p

February 14·44 0·000 2·85 0·681 14·64 0·000 21·67 0·000 1·81 0·449 March 25·26 0·000 15·91 0·026 25·00 0·000 25·98 0·000 9·34 0·000 April 18·59 0·000 1·19 0·864 8·02 0·000 7·70 0·022 20·93 0·694 May 24·26 0·000 18·53 0·010 18·85 0·000 14·25 0·000 7·95 0·001 June 11·06 0·000 5·46 0·434 9·33 0·000 210·81 0·001 0·93 0·695 July 10·68 0·000 9·74 0·168 9·73 0·000 8·02 0·017 1·87 0·435 August 23·12 0·000 10·69 0·131 24·68 0·000 20·36 0·000 13·50 0·000 September 12·68 0·000 14·25 0·046 13·50 0·000 7·70 0·022 22·32 0·327 October 2·35 0·374 16·86 0·019 10·17 0·000 5·73 0·087 28·40 0·000 November 5·36 0·044 22·33 0·002 3·66 0·063 4·48 0·180 26·99 0·003 December 229·72 0·000 0·48 0·945 211·06 0·000 213·76 0·000 230·79 0·000

a) % variation: is derived from the relative risk obtained from exponential ß. b) EQUA: ‘Equatorial’, TEMP: ‘Temperate’, CTB: ‘Central Tropical Brazil’, ETN: ‘Eastern Tropical Northeast’, ETZ: ‘Equatorial Tropical Zone’. Source: SINAN/SVS/MoH; IBGE. *January reference month. winter, specifically in August. Despite the fact that leprosy detection varies by region in Brazil, and despite the fact that it is on the general decline in the country,9–11 the seasonal variations we identified are independent of either of these factors. The Eastern Tropical Northeast climate and the ‘Caatinga’ biome, both located in the Brazilian Northeast, showed decreases in the variation of leprosy detection rates in the June (winter). It is believed that this is associated with the period of festivities in the area, including festivals honouring patron saints that allegedly influence the supply dynamics of healthcare services because they are large-scale tourist events.12

Table 4. Seasonality analysis of the detection rate of leprosy according to months of the year* by biomes, Brazil, 2008–2012

AM CAA ATLANTIC PAMPA CERR PANT Biomes Months %var p %var p %var p %var p %var p %var p

February 12·83 0·000 3·48 0·267 13·03 0·000 241·94 0·067 14·39 0·000 38·10 0·111 March 23·59 0·000 8·70 0·006 23·12 0·000 229·03 0·219 22·18 0·000 30·95 0·188 April 14·66 0·000 22·51 0·416 8·39 0·000 29·68 0·696 3·74 0·126 0·00 1·000 May 20·81 0·000 5·07 0·107 16·31 0·000 225·81 0·278 18·91 0·000 40·48 0·092 June 9·20 0·000 26·86 0·025 20·57 0·790 229·03 0·219 11·50 0·000 2·38 0·914 July 6·97 0·000 3·14 0·316 9·64 0·000 216·13 0·508 5·72 0·020 11·90 0·596 August 22·45 0·000 15·66 0·000 22·33 0·000 229·03 0·219 19·14 0·000 47·62 0·051 September 8·75 0·000 20·05 0·988 11·90 0·000 3·23 0·900 8·05 0·001 2·38 0·914 October 0·69 0·765 28·65 0·004 12·62 0·000 29·68 0·696 1·87 0·442 33·33 0·159 November 5·36 0·022 24·78 0·119 7·78 0·000 3·23 0·900 24·76 0·046 4·76 0·829 December 228·45 0·000 227·64 0·000 27·24 0·001 23·23 0·898 221·65 0·000 0·00 1·000

a) % variation: is derived from the relative risk obtained from exponential ß. b) AM: ‘Amazon’, CAA: ‘Caatinga’, ATLANTIC: ‘Atlantic Forest’, ‘Pampa’, CERR: ‘Cerrado’, PANT: ‘Pantanal’. Source: SINAN/SVS/MoH; IBGE. *January reference month. 540 A.C.A.A. Rocha et al. Although not measured in this study, the findings regarding seasonality may be related to the access to the healthcare in each region. It is important mention that Brazil presents only one public Health Insurance (Sistema U´ nico de Sau´de – SUS). Even though, each locality has independence to define strategies to improve the health surveillance that includes active search of new cases of leprosy.13 In the first months of the year, corresponding to late summer and early autumn, municipal managers are hiring primary healthcare professionals and meeting to develop action plans for their units. In addition, staff turnover, due to a demand for better working conditions and wages by physicians and professional nurses is a limiting factor for the healthcare system. Another limiting factor is the political interference in the appointment and retention of healthcare professionals.14 –15 Among the five regions, the North region covers the largest area of Brazil, and most municipalities there are hyper-endemic for leprosy.13 The rainy season occurs between spring and summer (November to March) and the dry season between autumn and winter (April to October).16 Although there are different climatic conditions between periods of drought and well-defined rain, the poor access to health services did not influence the seasonality of the leprosy detection rate, since most of the population resides in urban areas. This did, however, influence the findings of this study for the North region, the Equatorial climate, and the Amazon biome. According to the results of the Leprosy Elimination Monitoring (LEM) held in 2012 in Brazil the Southeast region is characterised by a greater distance between health services and leprosy patients, and it has an average of 4·5 consultations before a leprosy diagnosis is made. Services are specialised and centralised in health centres located in large urban centres,13,17 while in the North and Northeast regions the mean number of consultations is three. The South region has fewer health services and facilities capable of diagnosing leprosy,13 yet in our study it did not show variation in the leprosy detection rate, indicating that although the healthcare services are limited, they are available throughout the year.This region has the highest detection of Grade 2 leprosy in Brazil, characterised by physical disability that often accompanies late diagnosis of the disease.9,13 The highest increases in leprosy detection rate in the South region were observed in the October and November (spring). In the October and November (spring), a campaign to fight skin cancer18 may be influencing the increases in the detection of the disease compared to other regions of the country. In the Midwest region, the second most endemic, there is extensive decentralisation of care in almost 100% of the municipalities.13 Still, the seasonal variations were well marked, which is addressed by geographic region, the ‘Cerrado’ biome that occupies most of the municipalities, or by the Central Tropical Brazil climate. The decrease in the detection rate of leprosy observed in summer (December) for most of the surveyed geographic units seems to be related to periods of recess or vacation influencing primary care services. Usually this period comprises the second half of December to the first half of January. The only services available are urgent care and emergency services in secondary healthcare facilities such as emergency care units, ambulance stations, and hospitals. The lack of outpatient care during this period seems to contribute to the delayed diagnosis of leprosy and consequently in maintaining the chain of transmission of the disease. These findings highlight the importance of developing strategies for epidemiological surveillance in the geographic regions where the disease is endemic, in order to ensure a more effective use of resources in the active surveillance, early diagnosis, timely treatment and healing of this disease to reduce its chain of transmission. Although each geographic area has its own environmental and cultural particularities, surveillance, control, and prevention of Seasonality of leprosy 541 leprosy along with promotion of leprosy awareness across all of Brazil should be both consistent and permanent. The delay/access in the diagnosis of leprosy varies among geographic regions and is inversely proportional to the level of endemism as verified during the last exercise of Leprosy Monitoring Elimination carried out in the country (LEM). Considering a mean delay of 6 months from the onset of the first symptoms to the diagnosis, the increase identified in March to May (autumn) is possibly related to the appearance of the first signs/symptoms of leprosy in September to November (spring), while the peak seen in August (winter) could be related to manifestation of the disease in February (summer). This study was limited in part by the fact that the outcome variable was influenced by the date of confirmation of diagnosis. Other limitation is that the statistical seasonal models are not adjusted by confounding variables or at least probable confounding environmental variables as temperature and humidity. Nonetheless, the study has enabled the characterisation of territorial differences in seasonal leprosy detection rates in Brazil. The absence of seasonality in the ‘Pampa’ biome stems from the low endemism, with a mean of five new cases per year, and in the ‘Pantanal’ biome it stems from a low population density, with approximately 355,443 inhabitants living in an area of 210 km2.5 Identifying the seasonal pattern of a disease aids in the planning and implementation of strategies for surveillance, prevention and control of disease-related health problems among population.1–3 Regarding leprosy specifically, taking a seasonal approach related to climate and biome can aid in understanding aspects of transmission. We concluded that the detection rate of leprosy in Brazil has a seasonal pattern with specific variations between geographical regions, climates, and biomes. The highest peaks in the detection rates were observed in May (autumn) and in August (winter). These patterns may be related to cultural habits of the specific populations, environmental factors, in addition to the supply of health services.

Authors contribuitions

Aline Cristina Arau´jo Alcaˆntara Rocha e Eliane Ignotti – conception, data analyses, preparation of the manuscript; Wesley Jonatar Alves da Cruz – data analysis and geographical analysis; Washington Leite Junger – conception and data analysis.

References

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