The study was done in Bandiagara town, situated in central Mali in West Africa. A detailed description of the study site can be found elsewhere (17). Children aged from 3-59 months residing in Bandiagara benefited from SMC since 2016. IRS was implemented in all areas of Bandiagara town in 2017 and 2018.
A prospective cohort study interspersed with monthly cross-sectional surveys involving three hundred children was conducted from October 2017 to December 2018.
The study inclusion criteria were: aged between 6 months and 15 years at the time of screening, resident of Bandiagara town, good general health based on clinical evaluation, written informed consent obtained from the parent/guardian, and the availability in follow-up for the entire study duration. Exclusion criteria were: refusal to participate in the study, simultaneous participation in an interventional clinical trial, chronic medication with known anti-malarial activity (such as trimethoprim-sulfamethoxazole for prevention of AIDS-associated opportunistic infections), and any condition that in the opinion of the principal investigator would jeopardize the safety or rights of a participant in the trial or would render the participant unable to comply with the protocol.
Active and passive surveillance were conducted to capture the incidence of malaria infection and disease. Active surveillance consisted of scheduled monthly visits aimed at detecting asymptomatic malaria infection and anaemia. Clinical examination of the participants was performed by the study physician at enrolment and on a quarterly basis. Following standard protocols, finger-prick blood samples were collected monthly for malaria smears, measurement of haemoglobin level, and parasite genotyping from filter paper. Venous blood was collected at enrolment and at the time of each malaria clinical episode for molecular and immunological analyses.
Passive surveillance consisted of continuous availability of medical care at the Bandiagara Malaria Project (BMP) research clinic and Bandiagara District Hospital, where parents/guardians were instructed to consult whenever their child was sick. Children were then examined by a physician, and axillary temperature was checked (fever was defined as axillary temperature ≥37.5°C). Blood samples were collected for microscopic examination for malaria parasites (thick blood film). If malaria was confirmed by microscopy, the haemoglobin level was determined, and filter paper collected for parasite genotyping. Clinical malaria was defined by the presence of one of the following symptoms consistent with malaria: fever (subjective or measured), headache, nausea or vomiting, diarrhea or abdominal pain, join pain, chills, seizure, lethargy, coma associated with a positive Plasmodium asexual stage.
Asymptomatic malaria was defined by the presence of Plasmodium irrespective of the stage without the symptoms listed above.
Clinical malaria cases were treated with artemether + lumefantrine combination therapy according to the Malian National Malaria Control program (NMCP) guidelines.
Malaria and rainfall time-series
After aggregation on a weekly time scale, time series of the number of malaria episodes was plotted together with rainfalls measured at the local weather station in Bandiagara.
For asymptomatic malaria time-series, the monthly cumulated number of asymptomatic cases and measured rainfalls were plotted together.
Rainfall data were obtained from the local weather station. Microsoft Excel version 2016 was used for plotting time-series.
Case mapping and spatial clusters detection
At enrollment, each child’s household (i.e., the place where the child slept) was georeferenced using a tablet with Open Data Kit (ODK) platform (accuracy approximately within 10 m).
A Geographical Information System was developed for the study area that also included the Bandiagara house blocks and bodies of water in the area.
Google earth was used for digitization of road infrastructure and water collection, and the administrative boundaries of Bandiagara town. After digitization, data were exported to QGIS and ARC GIS software for map processing. Data from Google Earth Pro, which was in Keyhole Markup Language (KML) file format was converted to Shapefile (SHP) to facilitate georeferencing in the geographic coordinate system.
Using Quantum GISTM software (QGISTM) version 2.18.1, participant households were mapped according to their geographic coordinates. Numerous children, likely siblings of the same family, shared the same location. For each location, data were subsequently aggregated, and several variables were calculated: initial number of study participants, total number of recorded malaria episodes or symptomatic malaria cases. The spatial distribution of malaria risk was illustrated by choropleth mapping of the number of malaria episodes at the block level.
SaTScanTM software, version 9.6, using the Kulldorf method of retrospective space-time permutation and the Bernoulli purely spatial model was used to determine the spatial variability of malaria risk, a cluster analysis was performed using Kulldorff's statistics through the SaTScanTM software version 9.6 with Poisson model SaTScanTM version 9.6 (18,19) . This widely applied method (20,21) moves a circular or elliptic scanning window over the study area and compares observed and expected case numbers inside and outside this window in order to detect clusters and estimate risk ratios. Using daily malaria episodes at each location, a Bernoulli distribution model with 50% of the population at risk, and elliptic scanning windows, high or low risk purely spatial clusters were sought over the study period. The Relative-risk was defined as the ratio of observed to expected cases. Cluster significance (P-value) was computed with a likelihood ratio test provided by a Monte Carlo approach using 999 random simulations under the null hypothesis of no cluster. Statistically significant spatial clusters (P-value < 0.05) were subsequently mapped on QGISTM.
The study was conducted in compliance with the International Conference on Harmonization Good Clinical Practices, the Declaration of Helsinki and regulatory requirements of Mali. Details on the consent and the protocol approval process have been described elsewhere17. The study was approved by the institutional ethics committee of the Faculty of Medicine dentistry and pharmacy of the University of Sciences Techniques and Technologies of Mali.