Literacy and recent history of diarrhoea are predictive of plasmodium falciparum parasitaemia in Kenyan adults

Background - Malaria is one of the most serious health problems in Kenya. In 2004, the Kenya Medical Research Institute and the US Army Medical Research Unit – Kenya surveyed adults in Samburu, Malindi, and Busia districts to determine socioeconomic risk factors for infection. Methods - Sociodemographic, health, and antimalarial data were collected along with blood for malaria testing. A smear was considered negative only if no Plasmodium falciparum parasites were observed in 100 high-powered fields. Univariate analysis was performed with Pearson\u27s Chi-square test and univariate logistic regression. A multivariate logistic regression model was then created which included only variables found to be at least marginally significant in univariate analysis. Results - A total of 1,141 subjects were recruited: 238 from Samburu, 442 from Malindi, and 461 from Busia. Smear positivities for P. falciparum were 1.7% in Samburu, 7.2% in Malindi and 22.3% in Busia. Interdistrict differences were statistically significant (p \u3c 0.001) in univariate analysis and in a multivariate logistic regression model which included district, literacy, occupation, and recent illness as independent variables. In the model, literacy and recent diarrhoeal illness were positively and at least marginally significantly associated with parasitaemia (p = 0.023 and p = 0.067, respectively). Neither age, sex, occupation, history of malaria in the previous three months, nor use of antimalarials in the previous four weeks were significantly associated with parasitaemia. Conclusion - While district of residence was the variable most highly predictive for parasitaemia among Kenyan adults surveyed, both a recent history of diarrhoeal illness and literacy were at least marginally statistically significant predictors

Yellow Fever Outbreak, Imatong, Southern Sudan

In May 2003, the World Health Organization received reports about a possible outbreak of a hemorrhagic disease of unknown cause in the Imatong Mountains of southern Sudan. Laboratory investigations were conducted on 28 serum samples collected from patients in the Imatong region. Serum samples from 13 patients were positive for immunoglobulin M antibody to flavivirus, and serum samples from 5 patients were positive by reverse transcription–polymerase chain reaction with both the genus Flavivirus–reactive primers and yellow fever virus–specific primers. Nucleotide sequencing of the amplicons obtained with the genus Flavivirus oligonucleotide primers confirmed yellow fever virus as the etiologic agent. Isolation attempts in newborn mice and Vero cells from the samples yielded virus isolates from five patients. Rapid and accurate laboratory diagnosis enabled an interagency emergency task force to initiate a targeted vaccination campaign to control the outbreak

Seroprevalence and distribution of arboviral infections among rural Kenyan adults: A cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Arthorpod-borne viruses (arboviruses) cause wide-spread morbidity in sub-Saharan Africa, but little research has documented the burden and distribution of these pathogens.</p> <p>Methods</p> <p>Using a population-based, cross-sectional study design, we administered a detailed questionnaire and used ELISA to test the blood of 1,141 healthy Kenyan adults from three districts for the presence of anti-viral Immunoglobulin G (IgG) antibodies to the following viruses: dengue (DENV), West Nile (WNV), yellow fever (YFV), Chikungunya (CHIKV), and Rift Valley fever (RVFV).</p> <p>Results</p> <p>Of these, 14.4% were positive for DENV, 9.5% were WNV positive, 9.2% were YFV positive, 34.0% were positive for CHIKV and 0.7% were RVFV positive. In total, 46.6% had antibodies to at least one of these arboviruses.</p> <p>Conclusions</p> <p>For all arboviruses, district of residence was strongly associated with seropositivity. Seroprevalence to YFV, DENV and WNV increased with age, while there was no correlation between age and seropositivity for CHIKV, suggesting that much of the seropositivity to CHIKV is due to sporadic epidemics. Paradoxically, literacy was associated with increased seropositivity of CHIKV and DENV.</p

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Detection of Avian Influenza Viruses in Wild Waterbirds in the Rift Valley of Kenya Using Fecal Sampling

Highly pathogenic avian influenza virus A/H5N1 has been reported in 11 African countries. Migratory waterbirds have the potential of introducing A/H5N1 into east Africa through the Rift Valley of Kenya. We present the results of a wild bird surveillance system for A/H5N1 and other avian influenza viruses based on avian fecal sampling in Kenya. We collected 2630 fecal samples in 2008. Viral RNA was extracted from pools of 3–5 fecal samples and analyzed for presence of avian influenza virus RNA by real-time RT-PCR. Twelve (2.3%) of the 516 sample pools were positive for avian influenza virus RNA, 2 of which were subtyped as H4N6 viruses. This is the first report of avian influenza virus in wild birds in Kenya. This study demonstrates the success of this approach in detecting avian influenza virus in wild birds and represents an efficient surveillance system for avian influenza virus in regions with limited resources