ABSTRACT
Biosurveillance defines the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision making for action at all levels. Animal health surveillance is an important component within biosurveillance systems comprising a continuum of activities from detecting biological threats, to analyzing relevant data, to managing identified threats, and embracing a One Health concept. The animal health community can strengthen biosurveillance by adopting various developments such as increasing the alignment, engagement, and participation of stakeholders in surveillance systems, exploring new data streams, improving integration and analysis of data streams for decision-making, enhancing research and application of social sciences and behavioral methods in animal health surveillance, and performing timely evaluation of surveillance systems. The aim of this paper is to explore components of a biosurveillance system from an animal health perspective and identify opportunities for the animal health surveillance community to enhance biosurveillance. Structural and operational diagrams are presented to demonstrate the required components and relevant data of animal health surveillance as an effective part within a biosurveillance system.
ABSTRACT
Most COVID-19 affected resource-constrained settings have not ascertained their disease prevalence that pose a risk for global health. In wake of limited diagnostics and research capacity in such settings, this disease forecasting model provides an example to be adapted for evidence-based response efforts. Using officially reported data, this model forecasted COVID-19 prevalence in cosmopolitan cities. Several risk-mitigation strategies were analyzed for effectiveness in controlling disease incidence. Moreover, the reproduction rates to ascertain transmission, herd-immunity threshold, and performance of required laboratory tests were studied. The severe-critical cases were relatively low due to larger young population. Following any risk-mitigation strategy, at end of first wave, a susceptible population remained at risk of recurrent COVID-19 transmission. The herd-immunity threshold was in accordance with global estimates but would need careful monitoring based on adopted risk-mitigation strategy and variation in vaccines’ efficacy. A test-gap between performed vs required laboratory tests led to miss several cases from getting diagnosed. First of its kind, this study estimates sub-national COVID-19 prevalence in dense-urban living in low-middle income settings. Future response policies should consider such evidence to prevent recurrent COVID-19 waves of transmission. Unless sustained herd-immunity is achieved by effective immunization, risk of re-introduction to vulnerable population would remain.