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As Africa-wide malaria prevalence declines, an understanding of human movement patterns is essential to inform how best to target interventions. We fitted movement models to trip data from surveys conducted at 3-5 sites throughout each of Mali, Burkina Faso, Zambia and Tanzania. Two models were compared in terms of their ability to predict the observed movement patterns - a gravity model, in which movement rates between pairs of locations increase with population size and decrease with distance, and a radiation model, in which travelers are cumulatively absorbed as they move outwards from their origin of travel. The gravity model provided a better fit to the data overall and for travel to large populations, while the radiation model provided a better fit for nearby populations. One strength of the data set was that trips could be categorized according to traveler group - namely, women traveling with children in all survey countries and youth workers in Mali. For gravity models fitted to data specific to these groups, youth workers were found to have a higher travel frequency to large population centers, and women traveling with children a lower frequency. These models may help predict the spatial transmission of malaria parasites and inform strategies to control their spread.

BackgroundAs malaria prevalence declines in many parts of the world due to widescale control efforts and as drug-resistant parasites begin to emerge, a quantitative understanding of human movement is becoming increasingly relevant to malaria control. However, despite its importance, significant knowledge gaps remain regarding human movement, particularly in sub-Saharan Africa.MethodsA quantitative survey of human movement patterns was conducted in four countries in sub-Saharan Africa: Mali, Burkina Faso, Zambia, and Tanzania, with three to five survey locations chosen in each country. Questions were included on demographic and trip details, malaria risk behaviour, children accompanying travellers, and mobile phone usage to enable phone signal data to be better correlated with movement. A total of 4352 individuals were interviewed and 6411 trips recorded.ResultsA cluster analysis of trips highlighted two distinct traveller groups of relevance to malaria transmission: women travelling with children (in all four countries) and youth workers (in Mali). Women travelling with children were more likely to travel to areas of relatively high malaria prevalence in Mali (OR = 4.46, 95% CI = 3.42-5.83), Burkina Faso (OR = 1.58, 95% CI = 1.23-1.58), Zambia (OR = 1.50, 95% CI = 1.20-1.89), and Tanzania (OR = 2.28, 95% CI = 1.71-3.05) compared to other travellers. They were also more likely to own bed nets in Burkina Faso (OR = 1.77, 95% CI = 1.25-2.53) and Zambia (OR = 1.74, 95% CI = 1.34 2.27), and less likely to own a mobile phone in Mali (OR = 0.50, 95% CI = 0.39-0.65), Burkina Faso (OR = 0.39, 95% CI = 0.30-0.52), and Zambia (OR = 0.60, 95% CI = 0.47-0.76). Malian youth workers were more likely to travel to areas of relatively high malaria prevalence (OR = 23, 95% CI = 17-31) and for longer durations (mean of 70 days cf 21 days, p < 0.001) compared to other travellers.ConclusionsWomen travelling with children were a remarkably consistent traveller group across all four countries surveyed. They are expected to contribute greatly towards spatial malaria transmission because the children they travel with tend to have high parasite prevalence. Youth workers were a significant traveller group in Mali and are expected to contribute greatly to spatial malaria transmission because their movements correlate with seasonal rains and hence peak mosquito densities. Interventions aimed at interrupting spatial transmission of parasites should consider these traveller groups.

A study on all outpatients treated during first working day at government and mission health facilities were conducted. The purpose was to assess the association between use of microscopy and rapid antigen-detection diagnostic test (RDT) and the prescription of antimalarials.