Category Archives: Mapping

Pilot Mapping, Real Time Reporting and Responding in High Risk Malaria Areas of Viet Nam

Viet Nam is among the Asia-Pacific countries focusing on eliminating malaria. Mapping helps target malaria interventions. Nguyen Xuan Thang and colleagues (James O’Donnell, Vashti Irani, Leanna Surrao, Ricardo Ataide, Josh Tram, An Le, Sara Canavati, Tran Thanh Duong, Tran Quoc Tuy, Gary Dahl, Gerard Kelly, Jack Richards, Ngo Duc Thang) presented their pilot mapping efforts at the Malaria World Congress in Melbourne recently and below share their experiences with us.

Viet Nam is focused on eliminating malaria by 2030. Viet Nam saw a 73% reduction in cases between 2013 and 2017 (NIMPE data), yet border provinces still have a high burden of malaria. However, some provinces still have a high burden of malaria. To achieve malaria elimination, it is essential to deploy targeted interventions in these locations.

Spatial Decision Support Systems (SDSS) can be used by National Malaria programs to integrate geographic elements in the management of malaria cases and facilitate targeted malaria interventions in these high-risk settings.

The objective of this work was to pilot a SDSS system for Binh Phuoc and Dak Nong Provinces in Viet Nam to facilitate ongoing surveillance and targeted malaria, as part of the Regional Artemisinin-resistance Initiative (RAI). This objective was achieved by:

  • Collecting data with cell phones

    Collecting baseline GIS data at household level and environmental characteristics associated with the area;

  • Establishing a routine data collection system that will be reported by mobile medical staff by mobile phone;
  • Integrating this data to form a spatial decision support system (SDSS);
  • Using the SDSS system for direct reporting to malaria control programs that provided strategic solutions for the prevention of disease spread and the elimination of malaria

Sample cell phone data screens

In Phase 1, a household and mapping survey was conducted in collaboration with commune, district and village health workers. Epicollect5 software was used on smartphones with GPS functionality to record mapping information (latitude and longitude) and general information on household members. During Phase 1, 10,506 households were surveyed and data was aggregated in a custom Geographic Information System (GIS) database.

The majority of the surveyed individuals were of the Kinh ethnicity (19,282; 35.4%), followed by M’Nong (4,669; 8.6%) and Mong (3,359; 6.2%). Data related to malaria among mobile populations were included in the GIS as a means to identify and describe groups at high risk for malaria e.g. forest-goers. The survey data were reviewed, cleaned and matched using the ID numbers, then aggregated with relevant administrative boundary data and linked on ArcGIS 10.2 software. This database is located in a custom GIS system and can be visualized as a spatial transmission model to support appropriate decision-making

Dots representing households

Phase 2 focused on ongoing surveillance with rapid case reporting and responses. Malaria cases diagnosed at public and local health facilities were entered into the system by Commune Health Officials. Village Health Workers were immediately notified and went to the patient’s home to undertake case investigation including further household mapping and active case detection activities. The Viet Nam National Institute of Malariology was also notified, and organized local officials to carry out an investigation into the sources of transmission (i.e. ‘hotspots’) and to implement timely interventions.

Dots representing cases

When the cases were identified, Village Health Workers went to the patient’s home to undertake operational procedures including geographic exploration, household mapping to identify the location and to identify the list of affected households. They also collected this data on EpiCollect5. Collated information on cases, transmission point, zoning of the target villages allowed for early detection of malaria outbreaks. The National Institute of Malariology can also issue guidelines when the hotspots are identified and when disease outbreaks occur

These activities are ongoing. In conclusion, a custom GIS database was developed using a household survey in Binh Phuoc and Dak Nong province of Viet Nam. Malaria cases were mapped to identify hotspots of malaria transmission and enable further active case detection and targeted interventions. This established GIS database aims to support routine case notification and to enhance the role of surveillance for active case detection and responses to achieve malaria elimination.

The authors are affiliated with the National Institute of Malariology, Parasitology, Entomology (NIMPE), Viet Nam; Burnet Institute, Australia; and Health Poverty Action, UK. Contact:

Mapping to Integrate Filariasis and Onchocerciasis Control with Malaria Interventions

William R Brieger ( and Gilbert Burnham ( of The Johns Hopkins Bloomberg School of Public Health, Department of International Health presented ideas about mapping and integration of neglected tropical diseases and malaria interventions at the Malaria World Congress, Melbourne, Australia, July 2018

Overview: Lymphatic Filariasis (LF) and Malaria share a common vector in sub-Saharan Africa. Mass Drug Administration (MDA) is a strategy that is common to both diseases. Where the diseases overlap there is the potential opportunity to coordinate both vector control and MDA to achieve synergy in program results. The example of Burkina Faso, supplemented with information from Ghana, serves as an example of what could be integrated and what actually happens.

Background: Thirty years ago then veterinary drug, ivermectin, was found effective in controlling neglected tropical diseases (NTDs), specifically two human filarial diseases: onchocerciasis and lymphatic filariasis (LF). The drug manufacturer donates 300 million treatments annually to eliminate both diseases. Since then, annual community based mass drug administration (MDA) efforts have resulted in millions of treatments in endemic countries and great progress has been made toward elimination of transmission. Through observation and experimentation, ivermectin was found to kill malaria carrying mosquitoes when they bite people who have taken ivermectin making it a useful tool for vector control.

CHWs in Burkina Faso demonstrating how to measure height to determine ivermectin dosage

Community Health Workers’ Role: Current research is examining how dosing and timing of treatments may impact national malaria vector control efforts. Comparing maps between malaria and LF can be a starting point for adapting ivermectin MDAs for malaria vector control. Burkina Faso MDAs are operationalized by community health workers (CHWs) who are part of a national program that provides treatment for common illnesses and also conducts village level onchocerciasis and LF MDAs. Vector Control with Long Lasting Insecticide Treated Nets In most of rural Africa, malaria and lymphatic Filariasis are co-endemic and share the same anopheles mosquito vector.

However, that does not mean that there is a coordinated effort to plan distribution of LLINs despite the fact that the intervention meets the needs of both disease control efforts. The current NTD programs in Burkina Faso and Ghana focus on Preventive Chemotherapy (PCT) delivered through Mass Drug Administration (MDA). Vector Control is seen as essential in areas co-endemic with LF, Loa loa and Malaria – mapping helps identify priority areas for vector control.

Vector Control by Chance: In Ghana, the NTD/LF elimination program was unaware of the LLIN coverage data available in the NMCP housed in an adjacent building. This illustrates the lack of collaboration between the two programs. Thus where — and if — vector control benefits the reduction of both diseases, it is often by chance where LF is concerned.  The International NGO, The Carter Center, may be the only one that includes vector control as part of its programming for both malaria and LF in Nigeria. This practice should be replicated by other partners and country programs where possible.

Mass Drug Administration: MDA is the major strategy for control of five PCT diseases in the NTD program, and LF is one of those. Currently MDA anti-malarial drugs has been considered in limited situations in countries where there are areas that have very low transmission In the future countries may consider research that shows mosquitocidal effects of Onchocerciasis and LF MDAs with ivermectin. Otherwise for malaria, a special intervention called Seasonal Malaria Chemoprevention (SMC) is used in an MDA-like approach to reach young children in the African Sahel during high transmission months. In both cases, existing cadres of (usually volunteer) community health workers are the front line providers of MDA.

Burkina Faso LF Map from ESPEN: Mapping shows 10 of 70 health districts are currently doing LF MDA, though all have done it. Thus CHWs in all districts are experienced in ivermectin MDA. The malaria map shows that two-thirds of districts have a malaria incidence of 400/1000 or more while 14 have lower incidence. There is an overlap between current LF MDA districts and higher incidence malaria districts Both LF and Malaria Program Coverage can be seen to overlap in [program maps.

Ghana CHWs explain how they conduct MDA

Ghana Experiences: Ghana provides a contrasting example. There five regions in central Ghana that are mostly non-endemic for LF but do have moderate malaria transmission In the south two regions with former LF MDA activity overlap with higher malaria endemicity While four northern regions have lower malaria parasite prevalence, they do have current and recent LF MDAs Community Directed Distributors work with LF MDA in Ghana

Conclusions: Malaria elimination will need a mix of strategies to be successful. Therefore, it is not too early for malaria and NTD program managers, as well as their respective donors, to begin comparing maps to identify possibilities for adapting ivermectin MDAs for malaria vector control. Even though one endemic disease is nearing control or elimination, the infrastructure put in place to accomplish this can be mobilized for other disease control efforts – as long as we map where interventions and resources have been targeted.

High Resolution Malaria Risk Mapping in Mutasa District, Zimbabwe: Implications for Regaining Control

Mufaro Kanyangarara and her PhD thesis adviser, Luke Mullany of the Johns Hopkins Bloomberg School of Public Health Department of International Health, have been looking into the challenges of controlling and evCategorical maps of predicted household malaria risk and uncertaintyentually eliminating malaria in a multi-country context in southern Africa. We are sharing abstracts from her pioneering work including the following which explores high resolution risk mapping in Zimbabwe near the Mozambique border.

Background: In Zimbabwe, more than half of malaria cases are concentrated in Manicaland province, where malaria continues to rebound despite intensified control strategies. The objectives of this study were to develop a prediction model based on high-resolution environmental risk factors and obtain seasonal malaria risk maps for Mutasa District, one of the worst affected districts in Manicaland Province.

Methods: Household RDT status was obtained from ongoing community-based surveys in Mutasa District from October 2012 through April 2015. While environmental variables were extracted from remote sensing data sources and linked to household RDT status. Logistic regression was used to model the probability of household positivity as a function of the environmental covariates. Model prediction performance and overall model fit were examined. Model predictions and prediction standard errors were generated and inverse distance weighting was used to generate smoothed maps of malaria risk and prediction uncertainty by season.

Results: Between October 2012 and April 2015, 398 households participated in the household surveys. Ninety-six individuals representing 66 households tested RDT positive. Household malaria risk was significantly higher among households sampled during the rainy season and further from the Mozambique border, while malaria risk was lower in sparsely populated areas as well as households located at higher elevations during the rainy season. The resulting maps predicted elevated risk during the rainy season particularly in low-lying areas bordering with Mozambique. In contrast, the risk of malaria was low across the study area during the dry season with foci of malaria scattered along the northern, western and south-eastern peripheries of the study area.

Conclusion: This study provides evidence for the significant heterogeneity of malaria, which was strongly linked to elevation, house density and proximity to the Mozambique border. These findings underscore the need for strong cross-border malaria control initiatives to complement country specific interventions.

Satellite Mapping, an important step toward malaria control and elimination in Nigeria

Omede Ogu of Nigeria’s Federal Ministry of Health reports on efforts to undertake mapping of malaria in the country as a basis for better planning of control and eventual elimination efforts.

surface water 1The National Malaria Elimination Program (NMEP) has been meeting with the team from the National Space Research and Development Agency (NASRDA). Progress on pilot malaria mapping in Niger State is being reviewed, though the study is yet to be concluded. NMEP is also looking at opportunities that exist to expand their initial mapping to cover the whole of the country. Discussions are underway on next steps and development of a road map or a framework for the study going forward.

NASRDA explained that the current mapping effort was aimed is to use satellite-based technology to map surface water for Malaria Control in North-central Nigeria with Niger State as a Pilot study. They noted that data in inaccessible locations such as the marshy areas, thick forests, rugged terrain etc. were previously unavailable for relevant environmental policy and decision making in the region and Nigeria.

In addition is will be possible to do infrastructural mapping and inventory of health care facilities, in order to identify and assess the state of health care facilities, how accessible and future areas of need provision of these facilities in the country.

So far NASRDA has identified settlements, and locations of hospitals and health centres throughout Niger State using Global Positioning System (GPS). They have also identified water bodies and wetlands locations throughout the state.

Finally they are developing a map of Surface Water and wetlands in the state showing these in relation to locations of settlements, hospitals and health centres. NMEP is planning to link with colleagues doing similar mapping in Kenya.

NMEP plans to have the final report of the study ready by October for dissemination. Major partners with funding lines in their 2014 work plans for this study are the National Primary Health Care Development Agency (NPHCDA) and NASRDA. Additional funding and support is being sought.

Kenya already is using its mapping to focus appropriate malaria interventions. All countries will benefit in better mapping for targeting their malaria control and elimination efforts.