With three years of funding from the UK Medical Research Council, this research project is principally the foundations of Ursula Dalrymple’s DPhil thesis within the Malaria Atlas Project. The main aims of this working group are to:
- Quantify the prevalence of malaria-attributable (MAF) and non-malarial fever (NMFI) amongst sub-Saharan African children
- Measure the treatment-seeking rate for MAF and NMFI across the African continent
- Measure the proportion of malaria infections that result in effective treatment, and quantifying the rates at which malaria infections go untreated for various reasons
- Estimate the decrease in blood haemoglobin concentration associated with a malaria infection, and quantify malaria’s contribution to the syndrome of anaemia across Africa.
# Our data sources
In collaboration with the ROAD-MAP team, we collate household survey data where respondents are asked about their fever and treatment history, and receive a parasite-based diagnosis for malaria and have their blood haemoglobin concentration measured. In addition to this, we pair our survey data with remotely-sensed variables collated by ROAD-MAP, to aid spatial prediction of metrics of interest.
# Quantifying fever prevalence
Suspected malaria cases in Africa increasingly receive a rapid diagnostic test (RDT) before antimalarials are prescribed. While this ensures efficient use of resources to clear parasites, the underlying cause of the individual’s fever remains unknown due to potential coinfection with a non-malarial febrile illness. Widespread use of RDTs does not necessarily prevent over-estimation of clinical malaria cases or sub-optimal case management of febrile patients. In a recent publication in the journal eLife, we presented a new approach that allows inference of the spatiotemporal prevalence of both Plasmodium falciparum malaria-attributable and non-malarial fever in sub-Saharan African children from 2006 to 2014. We estimate that 35.7% of all self-reported fevers were accompanied by a malaria infection in 2014, but that only 28.0% of those (10.0% of all fevers) were causally attributable to malaria. Most fevers among malaria-positive children are therefore caused by non-malaria illnesses. This refined understanding can help improve interpretation of the burden of febrile illness and shape policy on fever case management.
# Measuring treatment seeking rate
The rate at which febrile individuals seek care is a critical determinant of health system effectiveness for treating and resolving febrile illnesses, including malaria. For malaria, understanding the fraction of cases that seek care is also crucial for correctly interpreting data on reported cases as part of burden estimation processes. Currently, data on care seeking for fever is used as a proxy for malaria, but this ignores the possibility of treatment-seeking rates differing for malaria versus non-malaria febrile causes. We aim to use household survey data on fever positivity rate and treatment seeking behaviour in African children with a multinomial modelling approach to generate treatment-seeking rates for malaria-attributable and non-malarial febrile illness.
# Effective treatment rates
Using the refined understanding of symptomatic illness with malaria, coupled with household survey data on malaria and fever prevalence and treatment, we aim to quantify the proportion of malaria infections that receive a prompt and effective treatment, followed by adherence to treatment and subsequent cure.
# Quantifying the effect of malaria on anaemia
Anaemia, or reduction in blood haemoglobin concentration, is frequently associated with malaria infection. Anaemia is highly prevalent in sub-Saharan Africa, especially amongst children and women of reproductive age, but quantification of the contribution of malaria versus other causes of anaemia (e.g. dietary iron deficiency, helminth infection) has not previously been quantified. We aim to use household survey data on malaria infection status and blood haemoglobin concentration in children less than five years of age to quantify the rate at which haemoglobin concentration drops with any given malaria infection, and to measure proportion of anaemia cases that are malaria-attributable, stratified by the severity of anaemia through space and time in sub-Saharan Africa.