Human movement data for malaria control and elimination strategic planning.

Deepa K Pindolia,Andres J Garcia,David L Smith,Caroline O Buckee,Andrew J Tatem,Amy Wesolowski,Robert W Snow,Abdisalan M Noor

doi:10.1186/1475-2875-11-205

Abstract

Recent increases in funding for malaria control have led to the reduction in transmission in many malaria endemic countries, prompting the national control programmes of 36 malaria endemic countries to set elimination targets. Accounting for human population movement (HPM) in planning for control, elimination and post-elimination surveillance is important, as evidenced by previous elimination attempts that were undermined by the reintroduction of malaria through HPM. Strategic control and elimination planning, therefore, requires quantitative information on HPM patterns and the translation of these into parasite dispersion. HPM patterns and the risk of malaria vary substantially across spatial and temporal scales, demographic and socioeconomic sub-groups, and motivation for travel, so multiple data sets are likely required for quantification of movement. While existing studies based on mobile phone call record data combined with malaria transmission maps have begun to address within-country HPM patterns, other aspects remain poorly quantified despite their importance in accurately gauging malaria movement patterns and building control and detection strategies, such as cross-border HPM, demographic and socioeconomic stratification of HPM patterns, forms of transport, personal malaria protection and other factors that modify malaria risk. A wealth of data exist to aid filling these gaps, which, when combined with spatial data on transport infrastructure, traffic and malaria transmission, can answer relevant questions to guide strategic planning. This review aims to (i) discuss relevant types of HPM across spatial and temporal scales, (ii) document where datasets exist to quantify HPM, (iii) highlight where data gaps remain and (iv) briefly put forward methods for integrating these datasets in a Geographic Information System (GIS) framework for analysing and modelling human population and Plasmodium falciparum malaria infection movements.

Highlights

The recent increase in funding for malaria control through international health initiatives, such as The Global Fund to fight AIDS, Tuberculosis and Malaria (GFATM) and the President’s Malaria Initiative (PMI) [1,2], has lead to the reduction in transmission in several Plasmodium falciparum and Plasmodium vivax malaria endemic countries [3,4,5,6,7,8]
This review describes survey and other relevant data types to illustrate the importance of Human population movement (HPM) across different spatial and temporal scales that are relevant for P. falciparum malaria control and elimination assessments, and document where datasets exist to quantify these types of HPM
According to previous P. falciparum malaria-relevant HPM analyses done in Zanzibar [15], susceptible residents travelling from the low transmission environment of Zanzibar to higher transmission areas and returning with infections may be more likely to result in onward transmission in Zanzibar compared to Tanzanian residents travelling to Zanzibar, primarily due to the length of stay in high transmission location and duration of infectious period spent in Zanzibar [23]

Summary

Introduction

The recent increase in funding for malaria control through international health initiatives, such as The Global Fund to fight AIDS, Tuberculosis and Malaria (GFATM) and the President’s Malaria Initiative (PMI) [1,2], has lead to the reduction in transmission in several Plasmodium falciparum and Plasmodium vivax malaria endemic countries [3,4,5,6,7,8]. The number of incoming malaria-infected travellers each month or each year determines the "vulnerability" of an area (defined by the risks posed by imported infections, for example through influxes of infected individuals from higher to lower transmission areas) [15,16]. Each imported case presents a risk of initiating outbreaks, epidemics, or increasing local transmission levels in areas of high "receptivity" (the historical potential for vector transmission that determines the severity of local onward transmission) [16]. Zanzibar presently remains the only example where an extensive mathematical quantification of HPM and P. falciparum malaria importation has been undertaken and put into context for strategic planning through a complete elimination feasibility assessment [15,21,23,24]

Objectives

Discussion

Conclusion