A Novel Coronavirus and a Broad Range of Viruses in Kenyan Cave Bats.

BACKGROUND AND METHODS: To investigate virus diversity in hot zones of probable pathogen spillover, 54 oral-fecal swabs were processed from five bat species collected from three cave systems in Kenya, using metagenome sequencing. RESULTS: Viruses belonging to the Astroviridae, Circoviridae, Coronaviridae, Dicistroviridae, Herpesviridae and Retroviridae were detected, with unclassified viruses. Retroviral sequences were prevalent; 74.1% of all samples were positive, with distinct correlations between virus, site and host bat species. Detected retroviruses comprised Myotis myotis, Myotis ricketti, Myotis daubentonii and Galidia endogenous retroviruses, murine leukemia virus-related virus and Rhinolophus ferrumequinum retrovirus (RFRV). A near-complete genome of a local RFRV strain with identical genome organization and 2.8% nucleotide divergence from the prototype isolate was characterized. Bat coronavirus sequences were detected with a prevalence of 24.1%, where analyses on the ORF1ab region revealed a novel alphacoronavirus lineage. Astrovirus sequences were detected in 25.9%of all samples, with considerable diversity. In 9.2% of the samples, other viruses including Actinidia yellowing virus 2, bat betaherpesvirus, Bole tick virus 4, Cyclovirus and Rhopalosiphum padi virus were identified. CONCLUSIONS: Further monitoring of bats across Kenya is essential to facilitate early recognition of possibly emergent zoonotic viruses.

Strengthening global health security by improving disease surveillance in remote rural areas of low-income and middle-income countries.

The COVID-19 pandemic has underscored the need to strengthen national surveillance systems to protect a globally connected world. In low-income and middle-income countries, zoonotic disease surveillance has advanced considerably in the past two decades. However, surveillance efforts often prioritise urban and adjacent rural communities. Communities in remote rural areas have had far less support despite having routine exposure to zoonotic diseases due to frequent contact with domestic and wild animals, and restricted access to health care. Limited disease surveillance in remote rural areas is a crucial gap in global health security. Although this point has been made in the past, practical solutions on how to implement surveillance efficiently in these resource-limited and logistically challenging settings have yet to be discussed. We highlight why investing in disease surveillance in remote rural areas of low-income and middle-income countries will benefit the global community and review current approaches. Using semi-arid regions in Kenya as a case study, we provide a practical approach by which surveillance in remote rural areas can be strengthened and integrated into existing systems. This Viewpoint represents a transition from simply highlighting the need for a more holistic approach to disease surveillance to a solid plan for how this outcome might be achieved.

The intersection of land use and human behavior as risk factors for zoonotic pathogen exposure in Laikipia County, Kenya.

A majority of emerging infectious diseases (EIDs) are zoonotic, mainly caused through spillover events linked to human-animal interactions. We conducted a survey-based human behavioral study in Laikipia County, Kenya, which is characterized by a dynamic human-wildlife-livestock interface. Questionnaires that assessed human-animal interactions, sanitation, and illnesses experienced within the past year were distributed to 327 participants among five communities in Laikipia. This study aimed to 1) describe variation in reported high-risk behaviors by community type and 2) assess the relationship between specific behaviors and self-reported illnesses. Behavioral trends were assessed in R via Fisher's exact tests. A generalized linear mixed model with Lasso penalization (GLMMLasso) was used to assess correlations between behaviors and participants' self-reported illness within the past year, with reported behaviors as independent variables and reported priority symptoms as the outcome. Reported behaviors varied significantly among the study communities. Participants from one community (Pastoralist-1) were significantly more likely to report eating a sick animal in the past year (p< 0.001), collecting an animal found dead to sell in the past year (p<0.0001), and not having a designated location for human waste (p<0.0001) when compared to participants from other communities. The GLMMLasso revealed that reports of an ill person in the household in the past year was significantly associated with self-reported illness. Sixty-eight percent of participants reported that bushmeat is available within the communities. Our study demonstrates community-level variation in behaviors that may influence zoonotic pathogen exposure. We further recommend development of targeted studies that explore behavioral variations among land use systems in animal production contexts.

Africa's Nomadic Pastoralists and Their Animals Are an Invisible Frontier in Pandemic Surveillance.

The effects of COVID-19 have gone undocumented in nomadic pastoralist communities across Africa, which are largely invisible to health surveillance systems despite the fact that they are of key significance in the setting of emerging infectious disease. We expose these landscapes as a "blind spot" in global health surveillance, elaborate on the ways in which current health surveillance infrastructure is ill-equipped to capture pastoralist populations and the animals with which they coexist, and highlight the consequential risks of inadequate surveillance among pastoralists and their livestock to global health. As a platform for further dialogue, we present concrete solutions to address this gap.

Detection of novel coronaviruses in bats in Myanmar.

The recent emergence of bat-borne zoonotic viruses warrants vigilant surveillance in their natural hosts. Of particular concern is the family of coronaviruses, which includes the causative agents of severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and most recently, Coronavirus Disease 2019 (COVID-19), an epidemic of acute respiratory illness originating from Wuhan, China in December 2019. Viral detection, discovery, and surveillance activities were undertaken in Myanmar to identify viruses in animals at high risk contact interfaces with people. Free-ranging bats were captured, and rectal and oral swabs and guano samples collected for coronaviral screening using broadly reactive consensus conventional polymerase chain reaction. Sequences from positives were compared to known coronaviruses. Three novel alphacoronaviruses, three novel betacoronaviruses, and one known alphacoronavirus previously identified in other southeast Asian countries were detected for the first time in bats in Myanmar. Ongoing land use change remains a prominent driver of zoonotic disease emergence in Myanmar, bringing humans into ever closer contact with wildlife, and justifying continued surveillance and vigilance at broad scales.