Fine-scale spatial and temporal variation of clinical malaria incidence and associated factors in children in rural Malawi: a longitudinal study

Abstract

Background: Spatio-temporal variations in malaria burden are currently complex and costly to measure, but are important for decision-making. We measured the spatio-temporal variation of clinical malaria incidence at a fine scale in a cohort of children under five in an endemic area in rural Chikhwawa, Malawi, determined associated factors, and monitored adult mosquito abundance.

Methods: We followed-up 285 children aged 6-48 months with recorded geolocations, who were sampled in a rolling malaria indicator survey, for one year (2015-2016). Guardians were requested to take the children to a nearby health facility whenever ill, where health facility personnel were trained to record malaria test results and temperature on the child's sick-visit card; artemisinin-based combination therapy was provided if indicated. The cards were collected and replaced 2-monthly. Adult mosquitoes were collected from 2-monthly household surveys using a Suna trap. The head/thorax of adult Anopheles females were tested for presence of Plasmodium DNA. Binomial logistic regression and geospatial modelling were performed to determine predictors of and to spatially predict clinical malaria incidence, respectively.

Results: Two hundred eighty two children, with complete results, and 267.8 child-years follow-up time were included in the analysis. The incidence rate of clinical malaria was 1.2 cases per child-year at risk; 57.1% of the children had at least one clinical malaria case during follow-up. Geographical groups of households where children experienced repeated malaria infections overlapped with high mosquito densities and high entomological inoculation rate locations.

Conclusions: Repeated malaria infections within household groups account for the majority of cases and signify uneven distribution of malaria risk within a small geographical area.

Keywords: Entomological surveillance; Incidence rate; Malaria; Spatio-temporal heterogeneity.

Fig. 1

Flow diagram of participants followed-up in the study and the total child-years follow-up completed

Fig. 2

Spatial distribution of clinical malaria incidence, female mosquito density and EIR. The maps show the number of malaria cases (red dots, a) occurring per child with the location of the child in Focal Area B. Blue dots (b) represent the number of female Anopheles mosquitoes per location per night; green dots (c) represent the number of infectious female Anopheles mosquitoes per location per night (entomological inoculation rate)

Fig. 3

Temporal changes in weather and malaria incidence. The graph shows: a variations in monthly rainfall in mm, temperature in °C and relative humidity as percent; b mosquito density, and clinical malaria incidence. The incidence peaks during the rainy season with associated increase in humidity. Only weather data from Focal Area B is included

Fig. 4

The distribution of malaria incidence by quarter in Focal Area B. a Q1: September to November 2015. b Q2: December 2015 to February 2016. c Q3: March to May 2016. d Q4: June to August 2016