Recently, the World Health Organization (WHO) declared the human monkeypox virus disease an international health emergency. In the past decades, infectious disease epidemics have significantly impacted low- and middle-income countries (LMICs), with coronavirus disease-2019 (COVID-19) being the most recent. LMICs, particularly in Africa and Asia, responded reasonably well by strengthening health systems, including infection prevention and control strategies, laboratory systems, risk communication, and training of essential healthcare workers for surge capacity in preparation for and response to COVID-19. With the possibility of other epidemics, such as the current epidemic of human Monkeypox, a consolidated global response is required. This article discusses lessons learned from previous Ebola and COVID-19 outbreaks and also provides recommendations on how these lessons can be useful to strengthen monkeypox disease outbreak preparedness and response in LMIC.
The objective of disease surveillance and response is to improve the flow of information to monitor the spread of Infectious diseases, evaluate the effectiveness of control and preventive measures. This study assessed surveillance actors' knowledge and capacity to access and utilize relevant evidence from COVID-19 response data. The study was carried out in Anambra State. We adopted a pre-test and post-test design for the study. The population included all the surveillance actors in Anambra state, and the sample was 32 surveillance actors drawn from 42 initial invited actors via accidental sampling. Demographic data and pre-test were administered before the one-day intensive training. After the training, a post-test was administered. Data collected were analyzed using means and standard deviations, and the Chi-square test was used to determine relationships between categorical variables. The study results revealed that there is an increase in the mean of knowledge and capacity amongst the respondents. The findings of this study suggest that ICT competence relevant to data analysis and translating data into Evidence-Informed Decision making (EIDM) can be enhanced through training workshops. This study recommends a conscious effort to institutionalize training, capacity building, and mentoring for knowledge sharing and sustainability of EIDM.
Public Health Emergency Operation Centers are established to coordinate COVID-19 disease and other public health threats. Surveillance is pivotal in enabling countries to monitor disease patterns and trends, and the use of a Surveillance Outbreak Response Management and analysis system (SORMAS) helps with real-time cases. SORMAS users can notify health departments about new cases of epidemic-prone diseases, detect outbreaks, and simultaneously manage outbreaks. SORMAS is a management process system that supports supervisors to validate cases and control the spread of disease. These SORMAS features enable data analysis for stakeholders, local responders, and policymakers to analyze disease data and make informed decisions for efficient and effective responses. This paper examined national data on COVID-19. We computed the proportion of patients with COVID-19 disease in Nigeria and the 95% confidence interval (CI) for the COVID-19 attributable fraction. This study shows that the proportion of patients who had COVID-19 lies between 6.35% and 6.39%. The SORMAS platform has increased Nigeria's capacity for accurate and timely data reporting and response.
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