Investigation of rodent reservoirs of emerging pathogens in Côte d'Ivoire, West Africa

Background: One of the main health problems in West Africa remains upsurge of emerging pathogens. Ebola virus disease outbreak occurred in 2014 in Liberia, Guinea and Sierra Leone, Monkeypox virus in Nigeria in 2017 and most recently Lassa virus in Nigeria, Togo and Benin in 2018.  These pathogens have animal reservoirs as vectors for transmission. Proper investigation of the pathogens in their rodent vectors could help  reduce and manage their emergence and spread. Methodology: This study was conducted with an approval from the Côte d’Ivoire Bioethics Community. Small mammal trappings were carried out in  9 sites within three zones namely, peri-urban, peri-rural and protected areas. Liver, lung and kidney tissues from trapped small mammals were  sampled in accordance with the recommended conditions of biosafety and bioethics. The organs were transported in liquid nitrogen to the  laboratory. Molecular tests were used to detect pathogens. Orthopoxviruses and Monkeypox virus were detected in the organs by PCR using  consensus primers targeting the virus surface membrane haemagglutinin (HA) genes, while Leptospira species were detected by PCR using primers  targeting the rrs and lfb1 genes. Results: Out of 4930 night-traps, 256 (5.19%) small mammals were trapped including Crocidura, Rattus, Lophuromys, Praomys, Mus and Mastomys.  Leptospira species were detected in 6 genera from 7 study sites and the infected small mammals accounted for 13.3%. Leptospira sp was detected  mainly in the rodent vector genera Rattus (32.3%), Lophuromys (29.0%), and Praomys (16.1%). Three species of Leptospira were detected and  Leptospira interrogans was the most common frequent species (74.2%). Monkeypox virus was not detected from studied small mammals. Conclusion: The initial data from our investigation indicates the presence of Leptospira sp in rodent vectors, Rattus, Lophuromys and Praomys,  which are the potential small mammalian reservoirs of this pathogen in Cote d’Ivoire

Setting a baseline for global urban virome surveillance in sewage

The rapid development of megacities, and their growing connectedness across the world is becoming a distinct driver for emerging disease outbreaks. Early detection of unusual disease emergence and spread should therefore include such cities as part of risk-based surveillance. A catch-all metagenomic sequencing approach of urban sewage could potentially provide an unbiased insight into the dynamics of viral pathogens circulating in a community irrespective of access to care, a potential which already has been proven for the surveillance of poliovirus. Here, we present a detailed characterization of sewage viromes from a snapshot of 81 high density urban areas across the globe, including in-depth assessment of potential biases, as a proof of concept for catch-all viral pathogen surveillance. We show the ability to detect a wide range of viruses and geographical and seasonal differences for specific viral groups. Our findings offer a cross-sectional baseline for further research in viral surveillance from urban sewage samples and place previous studies in a global perspective

Setting a baseline for global urban virome surveillance in sewage

The rapid development of megacities, and their growing connectedness across the world is becoming a distinct driver for emerging disease outbreaks. Early detection of unusual disease emergence and spread should therefore include such cities as part of risk-based surveillance. A catch-all metagenomic sequencing approach of urban sewage could potentially provide an unbiased insight into the dynamics of viral pathogens circulating in a community irrespective of access to care, a potential which already has been proven for the surveillance of poliovirus. Here, we present a detailed characterization of sewage viromes from a snapshot of 81 high density urban areas across the globe, including in-depth assessment of potential biases, as a proof of concept for catch-all viral pathogen surveillance. We show the ability to detect a wide range of viruses and geographical and seasonal differences for specific viral groups. Our findings offer a cross-sectional baseline for further research in viral surveillance from urban sewage samples and place previous studies in a global perspective

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran