Key traveller groups of relevance to spatial malaria transmission: a survey of movement patterns in four sub-Saharan African countries

Abstract

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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-016-1252-3) contains supplementary material, which is available to authorized users.

Malaria Elimination Campaigns in the Lake Kariba Region of Zambia: A Spatial Dynamical Model

“…While the migration rate in scenario 12 is likely to be much higher than the true migration rate, this scenario demonstrates that outcome of an elimination program is highly dependent on the nature and extent of regional human movement. While efforts are beginning to be made to characterize relevant human migration patterns [22–24], understanding local geographies and conditions will ultimately be crucial for predicting whether an elimination program will succeed.…”

The Hitchhiking Parasite: Why Human Movement Matters to Malaria Transmission and What We Can Do About It

“…In sub-Saharan Africa, a recent survey in Mali, Burkina Faso, Zambia, and Tanzania [11] found that women traveling with children are a remarkably consistent group of travelers of relevance to malaria transmission ( Figure 1B). While this group is more likely to own a bed net in some countries, they are significantly more likely to travel to areas of high malaria prevalence in all countries surveyed.…”

“…Census-derived migratory movements have been shown to correlate with CDR-derived short-term movements in Mesoamerica, suggesting that census data could serve as a predictor for human movement at multiple scales [10]. Furthermore, detailed surveys recording movement patterns, demographic data, and cell phone usage behavior can help to correct for biases inherent in these data sets and to classify traveler groups with distinct malaria risk characteristics [11]. Each of these data sets is associated with its own biases and a research agenda is needed to understand those biases and prioritize surveillance protocols that will be operationally useful.…”

“…This is illustrated in Figure 1A, where, for example, if human movement is assumed to be equivalent to parasite movement, then human movement data will suggest that malaria importation mostly originates from population 2; however, it may in fact be dominated by human movement from population 3 due to the susceptibility of these travelers to mosquito bites. Evidence from surveys in sub-Saharan Africa and Southeast Asia suggests that there are groups of high-risk travelers with unique movement patterns [11,12] (Figure 1B). Therefore, one fundamental output from a surveillance program is to identify key groups whose movements contribute disproportionately to sustaining parasite transmission and/or the dispersal of drug-resistant parasites.…”

“…The children that accompany them are particularly susceptible to malaria infection and have less developed immune systems, enabling this traveler group to contribute greatly to parasite dispersal. The same survey highlighted youth workers as a key traveler group of relevance to parasite dispersal in Mali, largely due to their agricultural labor trips coinciding with the rainy season, when malaria risk is highest [11].…”