A Spaal Agent-Based Model of vagus for Malaria Epidemiology

Md. Zahangir Alam1, S. M. Niaz Arifin2, H. M. Al-Amin3, Mohammad Shafiul Alam3, M. Sohel Rahman1

1Department of Computer Science & Engineering (CSE), Bangladesh University of Engineering & Technology (BUET), Dhaka, Bangladesh

2Department of Computer Science and Engineering, University of Notre Dame, IN 46556, USA

3Internaonal Centre for Diarrhoeal Disease Research Bangladesh (icddr,b), Dhaka, Bangladesh BUET Agenda • Introducon • Model Development • Field Data Collecon • Verificaon and Validaon (V&V) • Results Malaria • One of the largest cause of global human mortality and morbidity • Occurs in 100+ countries • 3.3 billion people at risk Malaria • A -borne infecous disease • Caused by parasites of the genus Plasmodium • Transmied to humans via bites from infected female Anopheles mosquitoes (vectors) Anopheles • Anopheles is the primary vector of malaria transmission • Among approximately 430 Anopheles species, 30-40 are known as transmiers • Anopheles gambiae: transmits the most dangerous parasite Anopheles vagus • Anopheles vagus is another species that transmits another parasite Plasmodium vivax • 47% malaria cases in the Asia-Pacific Region due to P. vivax Anopheles vagus • An. vagus is widely distributed in Asia

Bangladesh Indonesia Philippines Cambodia Laos Sri Lanka China Malaysia Thailand Hong Kong Myanmar Vietnam India Nepal Study Area

A study site in the hill tract district of Bandarban, Bangladesh

Source: Google Maps Study Area Study Area Study Area

Agent Based Models (ABMs) • For malaria, ABMs have been used to model the basic behavior of individual mosquitoes and other aspects of the disease • At Notre Dame, we developed a conceptual entomological core model of the populaon dynamics of Anopheles gambiae • Several ABMs were also developed An ABM for An. vagus • In collaboraon with BUET, the Notre Dame Model is modified to develop an ABM for the populaon dynamics of Anopheles vagus • The ABM (An. vagus) can give us important insights regarding the control of P. vivax malaria in the Asia-Pacific Region ABMvagus: Contribuons • The life cycle modeling of An. vagus, based on its important biological parameters – From field data • Simulang the effect of temperature on the abundance of An. vagus • Verificaon and validaon of the model’s output against field data Life Cycle*

6pm-6am anytime Pupa (P) Larva (L) Egg (E) Aquatic Habitat n ...

6pm-6am anytime Pupa (P) Larva (L) Egg (E) Aquatic Habitat 2 6pm-6am 6pm-6am Emergence Oviposition

6pm-6am anytime Pupa (P) Larva (L) Egg (E) Aquatic Habitat 1

Aquatic phase

Adult phase Male

anytime 7pm-8pm 6pm-6am anytime Immature Mate Seeking Blood Meal Blood Meal Gravid (G) Adult (IA) (MS) Female Seeking (BMS) Digesting (BMD)

6pm-6am, if no eggs remaining

Gonotrophic cycle

*S. M. Niaz Arifin, Gregory R Madey, and Frank H Collins. Examining the impact of larval source management and inseccide-treated nets using a spaal agent-based model of Anopheles gambiae and a landscape generator tool. Malaria Journal, 12(1):290, 2013. ABMvagus vs. ABMgambiae

Feature (Aquac) ABMvagus ABMgambiae Egg development In normal temperature, Temperature-dependent 60% eggs are developed within 2 days, and the remaining 40% within 3 days Larval development & • Four sub-stages: 1st Temperature-dependent Daily Mortality Rate (DMR) instar, 2nd instar, 3rd instar & 4th instar, with different duraons • DMRs in each sub-stage are 15%, 10%, 10%, and 10%, respecvely Pupa development & • 40% pupae are developed Temperature-dependent DMR within the first 24 hours • rest 60% within the next 30 hours • DMR is 5% ABMvagus vs. ABMgambiae

Feature (Adult) ABMvagus ABMgambiae Immature Adult • 10% on the 6th day Temperature-dependent (emergence) • 10% on the 7th day • 40% on the 8th day • 30% on the 9th day • 10% on the 10th day Blood Meal Seeking • 8:30 pm: 0%, Connues unl a female • 9:30 pm: 13.67% gets blood meal or dies. • 10:30 pm: 15.83% The effecve me-window for host-seeking is 6.00 pm • 11:30 pm: 10.8% to 6.00 am • 12:30 am: 7.2% • 1:30 am: 0.72% • 2:30 am: 0% • 3:30 am: 0.72% • 4:30 am: 1.44% • 5:30 am: 35.25% • 6:30 am: 14.39% • 7:30 am: 0% ABMvagus: Model Features • Mosquitoes and aquac habitats are modeled as agents • A mosquito agent stays in each stage for certain duraon – Probabilisc transions to the next stage • Timestep: hourly • For each stage, the daily mortality rate (DMR) is obtained from field data – Mortality is applied aer it is converted to an hourly mortality rate Climate & Environment Factors • P. vivax malaria transmission depends on several factors – Including vector availability, bing rates, etc. • Influenced by weather and climate variables, especially temperature

• ABMvagus includes a temperature profile module – Daily temperature data are fed from the profile Field Data Collecon • Collected by Internaonal Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR,B) • In collaboraon with Johns Hopkins Malaria Research Instute Khan et al. Malaria Journal 2011, 10:124 Page 4 of 10 http://www.malariajournal.com/content/10/1/124 Study Area*

Figure 1 Map of Kuhalong (A) and Rajbila (B) showing geographic clusters used for surveillance.

Knowledge, attitude and practice Hiring of SWs was initiated in June 2009 and their Information was collected from each household to field work in Kuhalong began in October 2009. Field determine the socio economic status and to identify the work in Rajbila began in April 2010. The SWs in each knowledge, attitudes, and practices (KAP) of the families union were divided into five teams with two persons in in*Khan the areaet al with. regardMapping to malaria,hypoendemic malaria treatment,, seasonal malaria in rural Bandarban, each team. One team was designated to carry out the health seeking behaviour, and use of bed nets. The first DSS survey, three teams were designated for the active roundBangladesh: a prospecve surveillance of KAP surveys was administered at the same. Malaria Journal, 10:124, 2011. malaria surveillance and one team was designated to time as the initial DSS survey and subsequent KAP sur- conduct mosquito surveillance. The teams were super- veys are scheduled to be carried out periodically to vised at the first level by a Field Assistant (FA), and at observe changes over time. the second level by the Field Research Manager (FRM) and a medical officer (MO). The FA was selected from Field worker and supervisory staff among the SWs eight months after initiation of the pro- The field work was conducted by locally hired surveil- ject based on his/her performance in the field. The MO lance workers (SW). The SWs were hired through a was a local, qualified, physician who had completed competitive process (written and oral exams), with post-graduate studies in Public Health from Australia. nearly all being tribal people. Thus, the SWs spoke the local languages and were familiar with the customs and Consent process geographical features of the area. Most of them had Before initiating the field activities, an experienced Field worked in other non-government organizations and had Research Manager (FRM) was transferred from another some experience with data collection. project to help with communications with the commu- The workers were trained in the specific research nity. Being a tribal person with more than 20 years methods to be undertaken, including approaching and experience working in field projects with the ICDDRB, communicating with persons in the community, he was familiar with the local customs and language as obtaining informed consent, obtaining the relevant sur- well as with field epidemiologic methods. Together with vey information and filling in the forms properly, other project staff, he visited the communities and dis- weighing subjects, obtaining finger prick blood, pre- cussed the project with local leaders and administrative paration of blood slides, collection of blood using the officials. When the teams went to the households to rapid diagnostic kits, interpreting the results of the request their participationinthestudy,theyobtained rapid test, obtaining blood on filter paper for PCR, and the informed consent of the head of each household or mosquito trapping procedures. They were also trained his/her representative. This consent allowed for the col- in the appropriate use of anti-malarial drugs according lection of information for the Family Visit Register to the national guidelines as well as the guidelines for (FVR), which included the names of all the household referral of severe cases. Figure 2 illustrates the field members, the relationship with the household head, age work being conducted in this rural, forested area of and sex. A copy of consent form and completed FVR Bangladesh. were given to the head of the household. Field Data Collecon • Monthly female abundance: – An. jeyporiensis: 19%, – An. vagus: 17%, and – An. kochi: 14% • Weather Data: collected from Soil Resource Development Instute for Bandarban, Bangladesh Field Data Collecon

Searching mosquito larvae by the side of a rice field

Photo Credits: Internaonal Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR,B) Field Data Collecon

(c) an hoof print

(a) a bamboo pole (b) a puddle

Searching mosquito larvae

Photo Credits: Internaonal Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR,B) Field Data Collecon

(d) Searching mosquito (e) Rearing mosquito larvae from a cement larvae in cages at the tank (large arficial Bandarban field office container)

Photo Credits: Internaonal Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR,B) Verificaon & Validaon • ABM is verified through early tesng • Two early implementaons are compared: one with 12 stages and the other with 8 stages with temperature-dependent equaons • Also validated against field data (as described above) Results (Preliminary)

Figure: Female abundance in 4 years simulaon run. The annual paerns of An. vagus abundance is directly regulated by temperature. The x-axis denotes simulaon me (in days) and the y- axis denotes mosquito abundance. Results (Preliminary)

Figure: Model validaon. An. vagus abundances from the simulaons of three consecuve years are compared to field data. Simulated results are very close to field data. Summary • An ABM for Anopheles gambiae (Notre Dame) is modified to develop an ABM for Anopheles vagus (BUET) • Other dominant species (e.g., An. jeyporiensis and An. kochi) can be incorporated with relave ease

• Model Development • Field Data Collecon

• Verificaon and Validaon (V&V) • Preliminary Results Quesons? Thank you!