Discussion
fever, malaria, malarial illness, febrile illness, generalised, febrile
MALARIA, REGRESSION, FEBRILE ILLNESS
This study adds to the evidence that it is feasible for CHWs to offer malaria testing using mRDTs in the community. With the use of CHWs, large-scale malaria testing intervention can reach the underserved population who cannot afford to visit the health facilities for care and those who seek care in the retail sector. The existence of CHWs with the ability to test for malaria using mRDT provides a great opportunity; however, various factors may affect the demand and supply of testing using mRDT by CHWs.Here we examine the outcomes of a community-based malaria testing to understand how to improve intervention design and maximise the impact of such programmes. The analysis was organised around the target group (community members) and their uptake or demand for the diagnostic testing intervention, and the supply of testing by the CHWs responsible for delivering the intervention. We were able to separate the determinants of uptake of malaria diagnostic testing generally from the determinants of uptake of mRDT performed by a CHW. These contrasting but complementary analyses helped us identify bottlenecks to intervention coverage at the community level.Analysis of community survey data revealed that demand for malaria diagnostic testing before treating a fever was lower among adults and is positively associated with being in the highest wealth quintile (relative to the poorest), findings which are consistent with other published studies.From the perspective of CHWs delivering malaria testing, a strong association was not observed between demographic characteristics and testing volume, but we did note that CHWs with concurrent formal employment tested more patients on average than those without, which could indicate greater visibility or mobility in the community. It was also observed that the monthly testing volume increased when the number of households under a CHW’s purview exceeded 50, but we could not detect a significant increase beyond that when households exceeded 100, suggesting a threshold effect whereby more households created more demand for testing but the ability to meet the demand may be undermined by time constraints after some threshold beyond 100 households. Finally, we report that testing rates were higher in clusters with high mRDT positivity rates, possibly reflecting greater awareness of malarial illness or higher demand for malaria services in areas with higher malaria burden. This could also reflect higher confidence in a test among CHWs or community members who have experience with some tests turning positive as has been seen in the healthcare setting.A deeper analysis of CHW perception of the intervention was undertaken in a smaller random sample of participating CHWs. We show that testing volume is not affected by competing CHW-related priorities, but is associated with how they perceive their clients’ confidence in testing and the likelihood of the client accepting the mRDT result and advice. This aligns well with the picture from the demand side where we observe that confidence in an mRDT performed by a CHW is strongly associated with testing with a CHW.This study had several limitations. First, we are not able to estimate the effect of free testing on the uptake of testing. Considering the study used diagnosis-dependent subsidies to test the rational use of AL, a similar study that deploys free testing in the absence of a conditional voucher would be required to resolve this. Similarly, it could be important to compare the effect of an intervention that delivered both the test and the treatment through the CHW rather than using a voucher redeemable in the private sector. Second, although the survey data have provided valuable insight on understanding drivers to demand and supply of malaria testing, seeking provider (CHW) and patient perspectives in a qualitative framework could provide a richer understanding of the facilitating factors and barriers to scaling up such an intervention, particularly the ways in which preferences and changes in behaviour may influence uptake of the intervention. Finally, though our survey design used repeated cross-sectional sampling, it is possible that the same household and/or febrile individual was surveyed at multiple survey time points and any resulting association was not explicitly modelled in our regression analysis. Our results are based on a representative, randomly selected population sample of recent fevers. As a result, our findings could be generalised to other contexts or service delivery programmes working through CHWs in communities where care for febrile illness is provided through a heterogeneous landscape of private, public and retail venues.