Three months since the detection of the first COVID-19 case in Africa, almost all countries of the continent continued to report lower morbidity and mortality than the global trend, including Europe and North America. We reviewed the merits of various hypotheses advanced to explain this phenomenon, including low seeding rate, effective mitigation measures, population that is more youthful, favorable weather, and possible prior exposure to a cross-reactive virus. Having a youthful population and favorable weather appears compelling, particularly their combined effect; however, progression of the pandemic in the region and globally may dispel these in the coming months.

Epidemiologic data indicate a global distribution of anthrax outbreaks associated with certain ecosystems that promote survival and viability of Bacillus anthracis spores. Here, we characterized three anthrax outbreaks involving humans, livestock, and wildlife that occurred in the same locality in Kenya between 2014 and 2017. Clinical and epidemiologic data on the outbreaks were collected using active case finding and review of human, livestock, and wildlife health records. Information on temporal and spatial distribution of prior outbreaks in the area was collected using participatory epidemiology. The 2014–2017 outbreaks in Nakuru West subcounty affected 15 of 71 people who had contact with infected cattle (attack rate = 21.1%), including seven with gastrointestinal, six with cutaneous, and two with oropharyngeal forms of the disease. Two (13.3%) gastrointestinal human anthrax cases died. No human cases were associated with infected wildlife. Of the 54 cattle owned in 11 households affected, 20 died (attack rate = 37%). The 2015 outbreak resulted in death of 10.5% of the affected herbivorous wildlife at Lake Nakuru National Park, including 745 of 4,500 African buffaloes (species-specific mortality rate = 17%) and three of 18 endangered white rhinos (species-specific mortality rate = 16%). The species mortality rate ranged from 1% to 5% for the other affected wildlife species. Participatory epidemiology identified prior outbreaks between 1973 and 2011 in the same area. The frequency and severity of outbreaks in this area suggests that it is an anthrax hotspot ideal for investigating risk factors associated with long-term survival of anthrax spores and outbreak occurrence.

The impacts of vaccination on the transmission of Rift Valley fever virus (RVFV) have not been evaluated. We have developed a RVFV transmission model comprising two hosts—cattle as a separate host and sheep and goats as one combined host (herein after referred to as sheep)—and two vectors—Aedes species (spp) and Culex spp—and used it to predict the impacts of: (1) reactive vaccination implemented at various levels of coverage at pre-determined time points, (2) targeted vaccination involving either of the two host species, and (3) a periodic vaccination implemented biannually or annually before an outbreak. The model comprises coupled vector and host modules where the dynamics of vectors and hosts are described using a system of difference equations. Vector populations are structured into egg, larva, pupa and adult stages and the latter stage is further categorized into three infection categories: susceptible, exposed and infectious mosquitoes. The survival rates of the immature stages (egg, larva and pupa) are dependent on rainfall densities extracted from the Tropical Rainfall Measuring Mission (TRMM) for a Rift Valley fever (RVF) endemic site in Kenya over a period of 1827 days. The host populations are structured into four age classes comprising young, weaners, yearlings and adults and four infection categories including susceptible, exposed, infectious, and immune categories. The model reproduces the 2006/2007 RVF outbreak reported in empirical surveys in the target area and other seasonal transmission events that are perceived to occur during the wet seasons. Mass reactive vaccination strategies greatly reduce the potential for a major outbreak. The results also suggest that the effectiveness of vaccination can be enhanced by increasing the vaccination coverage, targeting vaccination on cattle given that this species plays a major role in the transmission of the virus, and using both periodic and reactive vaccination strategies. Reactive vaccination can be effective in mitigating the impacts of RVF outbreaks but practically, it is not always possible to have this measure implemented satisfactorily due to the rapid onset and evolution of RVF epidemics. This analysis demonstrates that both periodic and reactive vaccination ought to be used strategically to effectively control the disease. Evaluation of the relative impacts of RVF vaccination has not been previously carried out. We present a model that simulates RVFV transmission between two livestock hosts (cattle as a separate host and sheep referring to both sheep and goats) and two mosquito species (Aedes and Culex species). We then apply the model to evaluate policy-relevant impacts of vaccinating (1) different proportions of animals at different times to the simulated outbreak, (2) either of the host species, and (3) different proportions of animals in a periodic biannual or annual vaccination preventative strategy. Vector population growth is dependent on rainfall extracted from the Tropical Rainfall Measuring Mission (TRMM) for an RVF endemic site in Kenya over a period of 1827 days. The model reproduces the 2006/2007 RVF outbreak reported in empirical surveys in the target area and other seasonal transmission events that occur during the wet seasons. Consistent with anecdotal evidence, mass livestock vaccination can greatly reduce the potential for a major outbreak. The model predicts that the effectiveness can be improved by increasing the proportion of vaccinated animals, targeting vaccination against cattle and strategically augmenting periodic preventative strategies with reactive strategies once a RVF outbreak is predicted.

Background: Anthrax is an important zoonotic disease in Kenya associated with high animal and public health burden and widespread socio-economic impacts. The disease occurs in sporadic outbreaks that involve livestock, wildlife, and humans, but knowledge on factors that affect the geographic distribution of these outbreaks is limited, challenging public health intervention planning.Methods: Anthrax surveillance data reported in southern Kenya from 2011 to 2017 were modeled using a boosted regression trees (BRT) framework. An ensemble of 100 BRT experiments was developed using a variable set of 18 environmental covariates and 69 unique anthrax locations. Model performance was evaluated using AUC (area under the curve) ROC (receiver operating characteristics) curves.Results: Cattle density, rainfall of wettest month, soil clay content, soil pH, soil organic carbon, length of longest dry season, vegetation index, temperature seasonality, in order, were identified as key variables for predicting environmental suitability for anthrax in the region. BRTs performed well with a mean AUC of 0.8. Areas highly suitable for anthrax were predicted predominantly in the southwestern region around the shared Kenya-Tanzania border and a belt through the regions and highlands in central Kenya. These suitable regions extend westwards to cover large areas in western highlands and the western regions around Lake Victoria and bordering Uganda. The entire eastern and lower-eastern regions towards the coastal region were predicted to have lower suitability for anthrax.Conclusion: These modeling efforts identified areas of anthrax suitability across southern Kenya, including high and medium agricultural potential regions and wildlife parks, important for tourism and foreign exchange. These predictions are useful for policy makers in designing targeted surveillance and/or control interventions in Kenya.We thank the staff of Directorate of Veterinary Services under the Ministry of Agriculture, Livestock and Fisheries, for collecting and providing the anthrax historical occurrence data.

The majority of Kenya’s > 3 million camels have antibodies against Middle East respiratory syndrome coronavirus (MERS-CoV), although human infection in Africa is rare. We enrolled 243 camels aged 0–24 months from 33 homesteads in Northern Kenya and followed them between April 2018 to March 2020. We collected and tested camel nasal swabs for MERS-CoV RNA by RT-PCR followed by virus isolation and whole genome sequencing of positive samples. We also documented illnesses (respiratory or other) among the camels. Human camel handlers were also swabbed, screened for respiratory signs, and samples were tested for MERS-CoV by RT-PCR. We recorded 68 illnesses among 58 camels, of which 76.5% (52/68) were respiratory signs and the majority of illnesses (73.5% or 50/68) were recorded in 2019. Overall, 124/4692 (2.6%) camel swabs collected from 83 (34.2%) calves in 15 (45.5%) homesteads between April–September 2019 screened positive, while 22 calves (26.5%) recorded reinfections (second positive swab following ≥ 2 consecutive negative tests). Sequencing revealed a distinct Clade C2 virus that lacked the signature ORF4b deletions of other Clade C viruses. Three previously reported human PCR positive cases clustered with the camel infections in time and place, strongly suggesting sporadic transmission to humans during intense camel outbreaks in Northern Kenya.

Injecting drug use (IDU) is a key driver of the HIV epidemic particularly when individuals experience psychosocial conditions and risky sexual behavior in a syndemic manner. This study sets out to assess evidence of a syndemic pattern of psychosocial conditions (IDU, depression, intimate partner violence (IPV)) on one the hand and risky sexual behavior on the other while accounting for the socio-economic disadvantage among women who inject drugs (WWID) in low-income urban settings in Kenya. Using a cross-sectional study design, this study recruited 306 WWIDs from two sites in Nairobi between January 2017 and July 2017. Multiple methodologies including descriptive analyses of co-occurrences of psychosocial conditions at the individual level, standard logistic regression analyses to examine relationships and interactions within and between psychosocial conditions and risky sexual behavior, and classification trees algorithm for predictive modeling via machine learning were employed. The prevalence of the psychosocial conditions was as follows: IDU, 88%; depression, 77.1%; and IPV, 84%. The prevalence of risky sexual behavior was 69.3%. IDU and depression were related to each other (P < 0.05) and each of them with risky sexual behavior (P < 0.05). The highest 2-way and 3-way co-occurrence of conditions were reported in IDU and depression (72%) and in IDU, depression, and risky sexual behavior (62%), respectively, indicating clustering of the conditions at the individual level. Further, each additional psychosocial condition (IDU and depression) was associated with sixfold odds (P = 0.000) of having risky sexual behavior suggesting a dose-response relationship. Logistic regression analyses incorporating multiplicative interactive effects returned three significant variables (P < 0.05): IDU*depression interaction effect, “Age when delivered the first child,” and “Income.” Classification tree modeling represented a 5-level interaction analysis with IDU and depression predicted to have the highest influence on risky sexual behavior. Findings provide possible evidence of a syndemic pattern involving IDU, depression, and risky sexual behavior suggesting the need for an integrated approach to the implementation of harm reduction interventions among WWID in low-income urban settings in Kenya. This work highlights the need for further studies to authenticate the findings and to characterize pathways in the syndemic development in WWID.