Journal Article

Using parasite genetic and human mobility data to infer local and cross-border malaria connectivity in Southern Africa

Smith, Jennifer L, Alegana, Victor A, Chen, Anna, Ruktanonchai, Nick W, Tatem, Andrew J, Smith, David L, Bennett, Adam, Murphy, Maxwell, Greenhouse, Bryan, Cohen, Justin M, Mupiri, Anna-Rosa, Sturrock, Hugh JW, Mumbengegwi, Davis R, Didier, Bradley, Wesolowski, Amy, Gosling, Roland, Tessema, Sofonias, Hsiang, Michelle S, Wilheim, Jordan, Tambo, Munyaradzi

2019

Overview

Local and cross-border importation remain major challenges to malaria elimination and are difficult to measure using traditional surveillance data. To address this challenge, we systematically collected parasite genetic data and travel history from thousands of malaria cases across northeastern Namibia and estimated human mobility from mobile phone data. We observed strong fine-scale spatial structure in local parasite populations, providing positive evidence that the majority of cases were due to local transmission. This result was largely consistent with estimates from mobile phone and travel history data. However, genetic data identified more detailed and extensive evidence of parasite connectivity over hundreds of kilometers than the other data, within Namibia and across the Angolan and Zambian borders. Our results provide a framework for incorporating genetic data into malaria surveillance and provide evidence that both strengthening of local interventions and regional coordination are likely necessary to eliminate malaria in this region of Southern Africa. The number of malaria cases has dropped in some Southern Africa countries, but others still remain seriously affected. When people travel within and between countries, they can bring the parasites that cause the disease to different areas. This can fuel local transmission or even lead to outbreaks in a malaria-free area. When new malaria patients are diagnosed, they are often asked to report their recent travel history, so that the origin of their infection can be tracked. In theory, this would help to spot regions where the disease is imported from, and design targeted interventions. However, it is difficult to know exactly where the parasites come from based on self-disclosed travel history. At best, this history can provide information about that person's infection but nothing further in the past; at worst this history can be completely incorrect. Parasite DNA, on the other hand, has the potential to bring with it an indelible record of the past. To address the problem of determining where malaria infections came from, Tessema, Wesolowski et al. focused on Northern Namibia, a region where malaria persists despite being practically absent from the rest of the country. Patients movements were assessed using mobile phone call records as well as self-reported travel history In addition, samples from a single drop of blood were taken so that the genetic information of the parasites could be examined. Combining genetic data with travel history and phone records, Tessema, Wesolowski et al. found that, in Northern Namibia, most people had gotten infected by malaria locally. However, the genetic analyses also revealed that certain infections came from places across the Angolan and Zambian borders, information that was much more difficult to obtain using self-report or mobile phone data. A new, separate study by Chang, Wesolowski et al. also supports these results, showing that, in Bangladesh, combining genetic data with travel history and mobile phone records helps to track how malaria spreads. Overall, the work by Tessema, Wesolowski et al. indicate that, in Northern Namibia, it will be necessary to strengthen local interventions to eliminate malaria. However, different countries in the region may also need to coordinate to decrease malaria nearby and reduce the number of cases coming into the country. While genetic data can help to monitor how new malaria cases are imported, this knowledge will be most valuable if it is routinely collected across countries. New tools will also be required to translate genetic data into information that can easily be used for control and elimination programs.

• Publisher: eLife Science Publications, Ltd,eLife Sciences Publications Ltd,eLife Sciences Publications, Ltd
• Subject: Cellular telephones / Communicable Diseases, Imported - epidemiology / Communicable Diseases, Imported - parasitology / Disease transmission / Disease Transmission, Infectious / DNA / Epidemiological Monitoring / Epidemiology / Epidemiology and Global Health / Estimates / Genetic aspects / genetic epidemiology / Genetic research / Genotyping Techniques / History / Human Migration / Humans / Importation / Infections / Intelligence gathering / Malaria / Malaria - epidemiology / Malaria - parasitology / Medical research / Mobility / Molecular Epidemiology / Namibia - epidemiology / parasite genomics / Parasites / Pediatrics / Plasmodium - classification / Plasmodium - genetics / Plasmodium - isolation & purification / Population / Surveillance / Topography, Medical / Travel