Infectious Disease

Issiaka Soulama of Groupe de Recherche Action en Santé in Burkina Faso will build a molecular surveillance platform for monitoring the emergence and spread of different strains of the malaria-causing parasite, Plasmodium falciparum, including drug-resistant ones, to support the National Malaria Control Program and improve the control of malaria. They will develop a web-based platform so that when a person tests positive at one of the existing monitoring sites, they can quickly and easily record the location of the infection.

Moses Laman of the Papua New Guinea Institute of Medical Research will extend the national malaria surveillance platform, which maps infections across Papua New Guinea, to incorporate valuable genomic data of the malaria-causing parasites that can be used to better guide control and elimination efforts.

Jaishree Raman of the National Institute for Communicable Diseases in South Africa will integrate a genomic surveillance platform with the existing routine malaria surveillance program to better identify the source of infections and monitor parasite spread within South and southern Africa. Eliminating malaria requires knowing whether new infections are imported from other countries or are caused by local outbreaks, because they require different intervention strategies.

Elly Munde of the Hospital and Health Administration Services in Kenya will integrate a multiplex PCR assay into an existing malaria molecular surveillance program to detect a specific variant in the causative malaria parasite Plasmodium falciparum, which is undetectable by most rapid diagnostic tests and is threatening successful disease control. The specific haplotype of concern has a deletion of the genes encoding for histidine-rich proteins 2 and 3 (hrp2/3). Individuals infected with this haplotype produce a false negative result on most diagnostic tests.

Agaba Bosco from the Infectious Diseases Research Collaboration in Uganda will integrate a molecular surveillance system into their National Malaria Control Program to diagnose a currently under-detected variant of the causative parasite Plasmodium falciparum and better track spread. Most rapid diagnostic tests for malaria detect a specific parasite protein, however a new variant has emerged that has a deletion of the corresponding pfhrp2/3 gene, leading to a false negative test result.

Carl Marincowitz and colleagues at the University of Sheffield in the United Kingdom and the University of Cape Town in South Africa will develop a risk assessment tool to help emergency clinicians quickly decide whether a patient with suspected COVID-19 needs emergency care or can be safely treated at home to avoid overburdening hospitals particularly in low- and middle- income countries (LMICs).

Dale Barnhart and colleagues at Harvard Medical School in the U.S. and Partners in Health of Haiti, Malawi, Mexico, and Rwanda will determine how the COVID-19 pandemic has impacted health care provision and utilization for patients with HIV, heart disease, and diabetes, and the health outcomes of these patients, in all four countries. They will pool existing electronic medical data on chronic care patients collected from up to 30 health facilities in each country and create a harmonized database to identify the impacts of COVID-19 and any successful strategies used to improve care.

Juliane Foseca de Oliveira and colleagues at Fiocruz in Brazil will develop mathematical and statistical methods to model COVID-19 infection transmission, prevention and control across populations in Brazil to better inform local intervention efforts. Social and economic inequalities are known to shape the spread of diseases, therefore the team will integrate existing health data together with social and economic determinants for 5,570 Brazilian cities, as well as assessing data on the effects of the mitigation strategies and social mobility patterns.

Kirsty Le Doare and colleagues at the MRC/UVRI & LSHTM Uganda Research Unit and Makarere University John's Hopkins University in Uganda will develop a model using data collected in real-time to identify the risk factors for adverse pregnancy and infant outcomes caused by the COVID-19 pandemic that can be used to rapidly inform interventions. Lockdowns can severely impact women giving birth and access to maternal, neonatal, and child healthcare.

Maria Yury Ichihara and colleagues at the Centre for Data and Knowledge Integration for Health (Cidacs) at Fiocruz in Brazil will create a social disparities index to measure inequalities relevant to the COVID-19 pandemic, such as unequal access to healthcare, to identify regions that are more vulnerable to infection and to better focus prevention efforts. In Brazil, markers of inequality are associated with COVID-19 morbidity and mortality.