Circulation of SARS-CoV-2 and co-infection with Plasmodium falciparum in Equatorial Guinea
Lopez-Farfan, D.; Ncogo, P.; Oki, C.; Riloha, M.; Ondo, V.; Cano-Jimenez, P.; Martinez-Martinez, F. J.; Comas, I.; Irigoyen, N.; Berzosa, P.; Llanes, A. B.; Gomez-Diaz, E.
Show abstract
The impact of COVID-19 in Africa has been a big concern since the beginning of the pandemic. However, low incidence of COVID-19 case severity and mortality has been reported in many African countries, although data are highly heterogeneous and, in some regions, like Sub-Saharan Africa, very scarce. Many of these regions are also the cradle of endemic infectious diseases like malaria. The aim of this study was to determine the prevalence of SARS-CoV-2, the diversity and origin of circulating variants as well as the frequency of co-infections with malaria in Equatorial Guinea. For this purpose, we conducted antigen diagnostic tests for SARS-CoV-2, and microscopy examinations for malaria of 1,556 volunteers at six health centres in Bioko and Bata from June to October 2021. Nasopharyngeal swab samples were also taken for molecular detection of SARS-COV-2 by RT-qPCR and whole genome viral sequencing. We report 3.0% of SARS-CoV-2 and 24.4% of malaria prevalence over the sampling in Equatorial Guinea. SARS-CoV-2 cases were found at a similar frequency in all age groups, whereas the age groups most frequently affected by malaria were children (36.8% [95% CI 30.9-42.7]) and teenagers (34.7% [95% CI 29.5-39.9]). We found six cases of confirmed co-infection of malaria and SARS-CoV-2 distributed among all age groups, representing a 0.4% frequency of co-infection in the whole sampled population. Interestingly, the majority of malaria and SARS-CoV-2 co-infections were mild. We obtained the genome sequences of 43 SARS-CoV-2 isolates, most of which belong to the lineage Delta (AY.43) and that according to our pandemic-scale phylogenies were introduced from Europe in multiple occasions (7 transmission groups and 17 unique introductions). This study is relevant in providing first-time estimates of the actual prevalence of SARS-CoV-2 in this malaria-endemic country, with the identification of circulating variants, their origin, and the occurrence of SARS-CoV-2 and malaria co-infection.
Matching journals
The top 10 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Impact of seasonal malaria chemoprevention timing on clinical malaria incidence dynamics in the Kedougou region, Senegal 94%
- Current sampling and sequencing biases of Lassa mammarenavirus limit inference from phylogeography and molecular epidemiology in Lassa Fever endemic regions 93%
- Characterisation of populations at risk of sub-optimal dosing of artemisinin-based combination therapy in Africa 92%
Similar papers in this journal
- The evolution of dengue-2 viruses in Malindi, Kenya and greater East Africa: epidemiological and immunological implications 93%
- A novel metabarcoded DNA sequencing tool for the detection of Plasmodium species in malaria positive patients 93%
- SARS-CoV-2 introduction and lineage dynamics across three epidemic peaks in Southern Brazil: massive spread of P.1 92%
Similar papers in this journal
- Phylodynamic analysis of SARS-CoV-2 spread in Rio de Janeiro, Brazil, highlights how metropolitan areas act as dispersal hubs for new variants 95%
- Phylogenomics of Mycobacterium africanum reveals a new lineage and a complex evolutionary history 94%
- Population genomics of Bacillus anthracis from an anthrax hyperendemic area reveals transmission processes across spatial scales and unexpected within-host diversity 94%
Similar papers in this journal
- Spatiotemporal dynamics and epidemiological impact of SARS-CoV-2 XBB lineages dissemination in Brazil in 2023 94%
- Deciphering the tangible spatio-temporal spread of a 25 years tuberculosis outbreak boosted by social determinants 94%
- Trypanosoma cruzi isolates naturally adapted to congenital transmission display a unique strategy of transplacental passage 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.