COVID-19 data reporting systems in Africa reveal insights for future pandemics.

Globally, countries have used diverse methods to report data during the COVID-19 pandemic. Using international guidelines and principles of emergency management, we compare national data reporting systems in African countries in order to determine lessons for future pandemics. We analyse COVID-19 reporting practices across 54 African countries through 2020. Reporting systems were diverse and included summaries, press releases, situation reports and online dashboards. These systems were communicated via social media accounts and websites belonging to ministries of health and public health. Data variables from the reports included event detection (cases/deaths/recoveries), risk assessment (demographics/co-morbidities) and response (total tests/hospitalisations). Of countries with reporting systems, 36/53 (67.9%) had recurrent situation reports and/or online dashboards which provided more extensive data. All of these systems reported cases, deaths and recoveries. However, few systems contained risk assessment and response data, with only 5/36 (13.9%) reporting patient co-morbidities and 9/36 (25%) including total hospitalisations. Further evaluation of reporting practices in Cameroon, Egypt, Kenya, Senegal and South Africa as examples from different sub-regions revealed differences in reporting healthcare capacity and preparedness data. Improving the standardisation and accessibility of national data reporting systems could augment research and decision-making, as well as increase public awareness and transparency for national governments.

Spillover of pH1N1 to swine in Cameroon: an investigation of risk factors.

BACKGROUND: The 2009 pH1N1 influenza pandemic resulted in at least 18,500 deaths worldwide. While pH1N1 is now considered to be in a post-pandemic stage in humans it has nevertheless spilled back into swine in at least 20 countries. Understanding the factors that increase the risk of spillover events between swine and humans is essential to predicting and preventing future outbreaks. We assessed risk factors that may have led to spillover of pH1N1 from humans to swine in Cameroon, Central Africa. We sampled swine, domestic poultry and wild birds for influenza A virus at twelve sites in Cameroon from December 2009 while the pandemic was ongoing, to August 2012. At the same time we conducted point-count surveys to assess the abundance of domestic livestock and wild birds and assess interspecific contact rates. Random forest models were used to assess which variables were the best predictors of influenza in swine. RESULTS: We found swine with either active pH1N1 infections or positive for influenza A at four of our 12 sites. Only one swine tested positive by competitive ELISA in 2011-2012. To date we have found pH1N1 only in the North and Extreme North regions of Cameroon (regions in Cameroon are administrative units similar to provinces), though half of our sites are in the Central and Western regions. Swine husbandry practices differ between the North and Extreme North regions where it is common practice in to let swine roam freely, and the Central and Western regions where swine are typically confined to pens. Random forest analyses revealed that the three best predictors of the presence of pH1N1 in swine were contact rates between free-ranging swine and domestic ducks, contact rates between free-ranging swine and wild Columbiformes, and contact rates between humans and ducks. Sites in which swine were allowed to range freely had closer contact with other species than did sites in which swine were kept penned. CONCLUSIONS: Results suggest that the practice of allowing swine to roam freely is a significant risk factor for spillover of influenza from humans into swine populations.

Cocoa, livelihoods, and deforestation within the Tridom landscape in the Congo Basin: A spatial analysis.

In the context of emerging international trade regulations on deforestation-free commodities, the drivers of households' deforestation in conservation landscapes are of interest. The role of households' livelihood strategies including cocoa production, and the effects of human-elephant conflict are investigated. Using a unique dataset from a survey of 1035 households in the Tridom landscape in the Congo basin, the spatial autoregressive model shows that: (1) Households imitate the deforestation decisions of their neighbors; (2) A marginally higher income from cocoa production-based livelihood portfolios is associated with six to seven times higher deforestation compared to other livelihood strategies with a significant spillover effect on neighboring households' deforestation. The increase in income, mainly from cocoa production-based livelihoods in open-access systems can have a negative effect on forests. Households with a higher share of auto-consumption are associated with lower deforestation. If economic development brings better market access and lower auto-consumption shares, this is likely to positively influence deforestation. Without proper land use planning/zoning associated with incentives, promoting sustainable agriculture, such as complex cocoa agroforestry systems, may lead to forest degradation and deforestation.

Predicting hotspots for influenza virus reassortment.

The 1957 and 1968 influenza pandemics, each of which killed ≈1 million persons, arose through reassortment events. Influenza virus in humans and domestic animals could reassort and cause another pandemic. To identify geographic areas where agricultural production systems are conducive to reassortment, we fitted multivariate regression models to surveillance data on influenza A virus subtype H5N1 among poultry in China and Egypt and subtype H3N2 among humans. We then applied the models across Asia and Egypt to predict where subtype H3N2 from humans and subtype H5N1 from birds overlap; this overlap serves as a proxy for co-infection and in vivo reassortment. For Asia, we refined the prioritization by identifying areas that also have high swine density. Potential geographic foci of reassortment include the northern plains of India, coastal and central provinces of China, the western Korean Peninsula and southwestern Japan in Asia, and the Nile Delta in Egypt.

Genomic analyses reveal poaching hotspots and illegal trade in pangolins from Africa to Asia.

The white-bellied pangolin (Phataginus tricuspis) is the world's most trafficked mammal and is at risk of extinction. Reducing the illegal wildlife trade requires an understanding of its origins. Using a genomic approach for tracing confiscations and analyzing 111 samples collected from known geographic localities in Africa and 643 seized scales from Asia between 2012 and 2018, we found that poaching pressures shifted over time from West to Central Africa. Recently, Cameroon's southern border has emerged as a site of intense poaching. Using data from seizures representing nearly 1 million African pangolins, we identified Nigeria as one important hub for trafficking, where scales are amassed and transshipped to markets in Asia. This origin-to-destination approach offers new opportunities to disrupt the illegal wildlife trade and to guide anti-trafficking measures.

Genomic vulnerability and socio-economic threats under climate change in an African rainforest bird.

Preserving biodiversity under rapidly changing climate conditions is challenging. One approach for estimating impacts and their magnitude is to model current relationships between genomic and environmental data and then to forecast those relationships under future climate scenarios. In this way, understanding future genomic and environmental relationships can help guide management decisions, such as where to establish new protected areas where populations might be buffered from high temperatures or major changes in rainfall. However, climate warming is only one of many anthropogenic threats one must consider in rapidly developing parts of the world. In Central Africa, deforestation, mining, and infrastructure development are accelerating population declines of rainforest species. Here we investigate multiple anthropogenic threats in a Central African rainforest songbird, the little greenbul (Andropadus virens). We examine current climate and genomic variation in order to explore the association between genome and environment under future climate conditions. Specifically, we estimate Genomic Vulnerability, defined as the mismatch between current and predicted future genomic variation based on genotype-environment relationships modeled across contemporary populations. We do so while considering other anthropogenic impacts. We find that coastal and central Cameroon populations will require the greatest shifts in adaptive genomic variation, because both climate and land use in these areas are predicted to change dramatically. In contrast, in the more northern forest-savanna ecotones, genomic shifts required to keep pace with climate will be more moderate, and other anthropogenic impacts are expected to be comparatively low in magnitude. While an analysis of diverse taxa will be necessary for making comprehensive conservation decisions, the species-specific results presented illustrate how evolutionary genomics and other anthropogenic threats may be mapped and used to inform mitigation efforts. To this end, we present an integrated conceptual model demonstrating how the approach for a single species can be expanded to many taxonomically diverse species.

Regional vulnerability for COVID-19 in Cameroon.

INTRODUCTION: few studies have assessed risk for coronavirus disease 2019 (COVID-19) within African countries. Here we examine differences in vulnerability to COVID-19 among the ten administrative regions and two major cities of Cameroon based on epidemiological risk factors and access to healthcare resources. METHODS: regional epidemiological and healthcare access vulnerability indices were created and compared with cumulative COVID-19 cases, case fatality rates, co-morbidities, and healthcare resources in Cameroon. RESULTS: based on epidemiological risk factors, populations in the East Region, Douala (in the Littoral Region), West Region, and Yaoundé (in the Center Region) are at highest risk for COVID-19. Meanwhile, the North, Far North, East, and Adamawa Regions had the most healthcare access vulnerability. COVID-19 cases per population were highest in the Center, Littoral, and East Regions. Case fatality rates were greatest in the North Region. Potential co-morbidities with greater prevalence among COVID-19 patients included male sex, hypertension, and diabetes. CONCLUSION: epidemiological risk factors for COVID-19 and access to healthcare varies between the regions of Cameroon. These discrepancies are potentially reflected in regional differences of COVID-19 cases and case fatality rates. In particular, the East Region has high epidemiological risk factors and low healthcare accessibility compared to other regions. Understanding the relationships between epidemiological risk factors, access to healthcare resources, and COVID-19 cases in Cameroon could aid decision-making among national policymakers and inform further research.

Coquillettidia (Culicidae, Diptera) mosquitoes are natural vectors of avian malaria in Africa.

BACKGROUND: The mosquito vectors of Plasmodium spp. have largely been overlooked in studies of ecology and evolution of avian malaria and other vertebrates in wildlife. METHODS: Plasmodium DNA from wild-caught Coquillettidia spp. collected from lowland forests in Cameroon was isolated and sequenced using nested PCR. Female Coquillettidia aurites were also dissected and salivary glands were isolated and microscopically examined for the presence of sporozoites. RESULTS: In total, 33% (85/256) of mosquito pools tested positive for avian Plasmodium spp., harbouring at least eight distinct parasite lineages. Sporozoites of Plasmodium spp. were recorded in salivary glands of C. aurites supporting the PCR data that the parasites complete development in these mosquitoes. Results suggest C. aurites, Coquillettidia pseudoconopas and Coquillettidia metallica as new and important vectors of avian malaria in Africa. All parasite lineages recovered clustered with parasites formerly identified from several bird species and suggest the vectors capability of infecting birds from different families. CONCLUSION: Identifying the major vectors of avian Plasmodium spp. will assist in understanding the epizootiology of avian malaria, including differences in this disease distribution between pristine and disturbed landscapes.

A Dynamical and Zero-Inflated Negative Binomial Regression Modelling of Malaria Incidence in Limpopo Province, South Africa.

Recent studies have considered the connections between malaria incidence and climate variables using mathematical and statistical models. Some of the statistical models focused on time series approach based on Box-Jenkins methodology or on dynamic model. The latter approach allows for covariates different from its original lagged values, while the Box-Jenkins does not. In real situations, malaria incidence counts may turn up with many zero terms in the time series. Fitting time series model based on the Box-Jenkins approach and ARIMA may be spurious. In this study, a zero-inflated negative binomial regression model was formulated for fitting malaria incidence in Mopani and Vhembe-two of the epidemic district municipalities in Limpopo, South Africa. In particular, a zero-inflated negative binomial regression model was formulated for daily malaria counts as a function of some climate variables, with the aim of identifying the model that best predicts reported malaria cases. Results from this study show that daily rainfall amount and the average temperature at various lags have a significant influence on malaria incidence in the study areas. The significance of zero inflation on the malaria count was examined using the Vuong test and the result shows that zero-inflated negative binomial regression model fits the data better. A dynamical climate-based model was further used to investigate the population dynamics of mosquitoes over the two regions. Findings highlight the significant roles of Anopheles arabiensis on malaria transmission over the regions and suggest that vector control activities should be intense to eradicate malaria in Mopani and Vhembe districts. Although An. arabiensis has been identified as the major vector over these regions, our findings further suggest the presence of additional vectors transmitting malaria in the study regions. The findings from this study offer insight into climate-malaria incidence linkages over Limpopo province of South Africa.

Phylogeny, biogeography and taxonomy of the African wattle-eyes (Aves: Passeriformes: Platysteiridae).

The African wattle-eyes (genera Platysteira and Dyaphorophyia) comprise 10 species endemic to Africa. We analyzed both mitochondrial and nuclear DNA sequence data to test the monophyly of this group and its two genera, provide a preliminary assessment of species limits, and gain insight into the phylogeographic history of the wattle-eye radiation. Analyses based on mitochondrial ND2 sequences failed to recover wattle-eye monophyly, but the alternatives were not well-supported. In contrast, analyses of two nuclear introns (myoglobin intron-2 and beta-fibrinogen intron-5) recovered wattle-eye monophyly, as did combined analyses of mitochondrial and nuclear data. These analyses, however, did not support reciprocal monophyly of the two wattle-eye genera typically recognized, suggesting instead that Platysteira is nested within a paraphyletic Dyaphorophyia. The diversification of most wattle-eye species and many subspecies occurred through the divergence of allopatric populations well before the Pleistocene. Species and subspecies with disjunct distributions are typically characterized by deep genetic divergences, suggesting that many of these populations are evolutionary independent and could be recognized as additional phylogenetic species. In D. castanea and D. chalybea, for example, divergent haplotypes from geographically disjunct populations were paraphyletic with respect to those of D. tonsa and D. jamesoni, respectively. Similarly, Platysteira laticincta is highly divergent from its sister taxon P. peltata ( approximately 9.5% ND2 sequence divergence), consistent with species level recognition of this endangered species. In contrast, more broadly distributed taxa inhabiting a greater diversity of habitats (e.g., P. peltata and P. cyannea) show evidence of gene flow and connectivity among regions, suggesting that previously isolated populations expanded and fused into one another. Our study provides a framework for additional analyses of intraspecific phylogeography and species limits in these colorful birds.

Exploring the Influence of Daily Climate Variables on Malaria Transmission and Abundance of Anopheles arabiensis over Nkomazi Local Municipality, Mpumalanga Province, South Africa.

The recent resurgence of malaria incidence across epidemic regions in South Africa has been linked to climatic and environmental factors. An in-depth investigation of the impact of climate variability and mosquito abundance on malaria parasite incidence may therefore offer useful insight towards the control of this life-threatening disease. In this study, we investigate the influence of climatic factors on malaria transmission over Nkomazi Municipality. The variability and interconnectedness between the variables were analyzed using wavelet coherence analysis. Time-series analyses revealed that malaria cases significantly declined after the outbreak in early 2000, but with a slight increase from 2015. Furthermore, the wavelet coherence and time-lagged correlation analyses identified rainfall and abundance of Anopheles arabiensis as the major variables responsible for malaria transmission over the study region. The analysis further highlights a high malaria intensity with the variables from 1998-2002, 2004-2006, and 2010-2013 and a noticeable periodicity value of 256-512 days. Also, malaria transmission shows a time lag between one month and three months with respect to mosquito abundance and the different climatic variables. The findings from this study offer a better understanding of the importance of climatic factors on the transmission of malaria. The study further highlights the significant roles of An. arabiensis on malaria occurrence over Nkomazi. Implementing the mosquito model to predict mosquito abundance could provide more insight into malaria elimination or control in Africa.

Climate warming causes declines in crop yields and lowers school attendance rates in Central Africa.

Although a number of recent studies suggest that climate associated shifts in agriculture are affecting social and economic systems, there have been relatively few studies of these effects in Africa. Such studies would be particularly useful in Central Africa, where the impacts of climate warming are predicted to be high but coincide with an area with low adaptive capacity. Focusing on plantain (Musa paradisiaca), we assess whether recent climate change has led to reduced yields. Analysis of annual temperature between 1950 and 2013 indicated a 0.8°C temperature increase over this 63-year period - a trend that is also observed in monthly temperatures in the last twenty years. From 1991 to 2011, there was a 43% decrease in plantain productivity in Central Africa, which was explained by shifts in temperature (R2=0.68). This decline may have reduced rural household wealth and decreased parental investment in education. Over the past two decades, there was a six month decrease in the duration of school attendance, and the decline was tightly linked to plantain yield (R2=0.82). By 2080, mean annual temperature is expected to increase at least 2°C in Central Africa, and our models predict a concomitant decrease of 39% in plantain yields and 51% in education outcomes, relative to the 1991 baseline. These predictions should be seen as a call-to-action for policy interventions such as farmer training programs to enhance the adaptive capacity of food production systems to mitigate impacts on rural income and education.

Translating Predictions of Zoonotic Viruses for Policymakers.

Recent outbreaks of Ebola virus disease and Zika virus disease highlight the need for disseminating accurate predictions of emerging zoonotic viruses to national governments for disease surveillance and response. Although there are published maps for many emerging zoonotic viruses, it is unknown if there is agreement among different models or if they are concordant with national expert opinion. Therefore, we reviewed existing predictions for five high priority emerging zoonotic viruses with national experts in Cameroon to investigate these issues and determine how to make predictions more useful for national policymakers. Predictive maps relied primarily on environmental parameters and species distribution models. Rift Valley fever virus and Crimean-Congo hemorrhagic fever virus predictions differed from national expert opinion, potentially because of local livestock movements. Our findings reveal that involving national experts could elicit additional data to improve predictions of emerging pathogens as well as help repackage predictions for policymakers.

Living with avian FLU--Persistence of the H5N1 highly pathogenic avian influenza virus in Egypt.

H5N1 highly pathogenic avian influenza virus (HPAIV) continues to cause mortality in poultry and threaten human health at a panzootic scale in Egypt since it was reported in 2006. While the early focus has been in Asia, recent evidence suggests that Egypt is an emerging epicenter for the disease. Despite control measures, epizootic transmission of the disease continues. Here, we investigate the persistence of HPAIV across wild passerine birds and domestic poultry between 2009 and 2012 and the potential risk for continuous viral transmission in Egypt. We use a new weighted cross J-function to investigate the degree and spatial temporal nature of the clustering between sightings of infected birds of different types, and the risk of infection associated with direct contact with infected birds. While we found no infection in wild birds, outbreaks occurred year round between 2009 and 2012, with a positive interaction between chickens and ducks. The disease was more present in the years 2010 and 2011 coinciding with the political unrest in the country. Egypt thus continues to experience endemic outbreaks of avian influenza HPAIV in poultry and an increased potential risk of infection to other species including humans. With the current trends, the elimination of the HPAIV infection is highly unlikely without a complete revamp of current policies. The application of spatial statistics techniques to these types of data may help us to understand the characteristics of the disease and may subsequently allow practitioners to explore possible preventive solutions.

Putative human and avian risk factors for avian influenza virus infections in backyard poultry in Egypt.

Highly pathogenic influenza A virus subtype H5N1 causes significant poultry mortality in the six countries where it is endemic and can also infect humans. Egypt has reported the third highest number of poultry outbreaks (n=1084) globally. The objective of this cross-sectional study was to identify putative risk factors for H5N1 infections in backyard poultry in 16 villages in Damietta, El Gharbia, Fayoum, and Menofia governorates from 2010-2012. Cloacal and tracheal swabs and serum samples from domestic (n=1242) and wild birds (n=807) were tested for H5N1 via RT-PCR and hemagglutination inhibition, respectively. We measured poultry rearing practices with questionnaires (n=306 households) and contact rates among domestic and wild bird species with scan sampling. Domestic birds (chickens, ducks, and geese, n=51) in three governorates tested positive for H5N1 by PCR or serology. A regression model identified a significant correlation between H5N1 in poultry and the practice of disposing of dead poultry and poultry feces in the garbage (F=15.7, p<0.0001). In addition, contact between domestic and wild birds was more frequent in villages where we detected H5N1 in backyard flocks (F=29.5, p<0.0001).

Pandemic A/H1N1/2009 influenza virus in swine, Cameroon, 2010.

Although swine origin A/H1N1/2009 influenza virus (hereafter "pH1N1″) has been detected in swine in 20 countries, there has been no published surveillance of the virus in African livestock. The objective of this study was to assess the circulation of influenza A viruses, including pH1N1 in swine in Cameroon, Central Africa. We collected 108 nasal swabs and 98 sera samples from domestic pigs randomly sampled at 11 herds in villages and farms in Cameroon. pH1N1 was isolated from two swine sampled in northern Cameroon in January 2010. Sera from 28% of these herds were positive for influenza A by competitive ELISA and 92.6% of these swine showed cross reactivity with pandemic A/H1N1/2009 influenza virus isolated from humans. These results provide the first evidence of this virus in the animal population in Africa. In light of the significant role of swine in the ecology of influenza viruses, our results call for greater monitoring and study in Central Africa.