The objective of this study was to describe the epidemiology of COVID-19 in Nigeria with a view of generating evidence to enhance planning and response strategies. A national surveillance dataset between 27 February and 6 June 2020 was retrospectively analysed, with confirmatory testing for COVID-19 done by real-time polymerase chain reaction (RT-PCR). The primary outcomes were cumulative incidence (CI) and case fatality (CF). A total of 40 926 persons (67% of total 60 839) had complete records of RT-PCR test across 35 states and the Federal Capital Territory, 12 289 (30.0%) of whom were confirmed COVID-19 cases. Of those confirmed cases, 3467 (28.2%) had complete records of clinical outcome (alive or dead), 342 (9.9%) of which died. The overall CI and CF were 5.6 per 100 000 population and 2.8%, respectively. The highest proportion of COVID-19 cases and deaths were recorded in persons aged 31–40 years (25.5%) and 61–70 years (26.6%), respectively; and males accounted for a higher proportion of confirmed cases (65.8%) and deaths (79.0%). Sixty-six per cent of confirmed COVID-19 cases were asymptomatic at diagnosis. In conclusion, this paper has provided an insight into the early epidemiology of COVID-19 in Nigeria, which could be useful for contextualising public health planning.

Introduction On March 17th, 2020, Oyo State recorded her first case of COVID-19 through a United Kingdom returnee. Oyo State Ministry of Health with the support of technical and development partners responded quickly and effectively to contain the outbreak. The outbreak was characterized by place, person and time. Methods Field investigations were conducted and contact tracing and follow up done, all confirmed cases were identified, line-listed and analyzed using Epi-info version 7. Results A total of 34 confirmed cases were identified all within the capital city of Oyo State and two transferred from other states. The mean age was 49.1 ± 2.0 years with over 40% within the age group 50-59 years. There were 11(35.5%) health care workers infection. The case-fatality was 6.5%. The epidemic curve initially shows a typical propagated pattern, followed by a point source; though atypical. Conclusion Outbreak of COVID-19 was confirmed in Oyo State. Field investigation provided information on the characteristics of persons, time and place. Intensified surveillance activities such as contact tracing and follow- up, drive through testing and active case search were useful in early case detection and control of the outbreak.

IntroductionContrary to World Health Organizations recommendations, health workers (HWs) still prescribe antimalarials to malaria rapid diagnostic test (mRDT)-negative patients, thus increasing overuse and the risk of parasite resistance to the antimalarials. The reasons for this are not clear. We identified factors associated with antimalarial prescription to mRDT-negative patients.MethodsWe conducted a cross-sectional study among 423 HWs. Data on socio-demographic characteristics, training, supervision experience and fever management practices were collected. We tested associations between independent variables and prescription of antimalarials to mRDT-negative patients using Chi square and logistic regression at p < 0.05.ResultsThe HWs were mostly community health workers (58.6%), with mean age of 41.0 (±8.8) years and 13.6 (± 9.0) years of professional practice. Females were 322 (76.1%) and 368 (87%) were married. Of the 423 HWs interviewed, 329 (77.8%) received training on mRDT use, 329 (80.6%) received supervision and 129 (30.5%) had good knowledge of causes of fever. Overall, 110 (26.0%) of the HWs prescribed antimalarials to mRDT-negative patients. A higher proportion of non-trained vs trained HWs [Adjusted Odds Ratio (aOR) = 4.9; 95% Confidence Interval (CI) (2.5-8.3)], and HWs having poor knowledge vs HWs having good knowledge of causes of fever [aOR = 1.9; 95% CI (1.0-3.5)], prescribed antimalarials to mRDT-negative patients.ConclusionHWs' lack of training on mRDT use and poor knowledge of causes of fever were associated with prescription of antimalarials to mRDT-negative patients. We recommend training on management of fever and mRDT use to reduce such inappropriate antimalarial prescriptions.

Aims: An outbreak of sudden deaths with clinical features suggestive of acute methanol poisoning was reported. An epidemiological investigation was conducted to verify the diagnosis and identify risk factors. Methodology: A joint team of officials of the Ondo State Ministry of Health, the World Health Organization, and the Nigerian Field Epidemiology and Laboratory Training Programme residents investigated the outbreak which was limited to two Local Government Areas of Ondo State, in Southwest Nigeria. An incident management coordination approach, modelled after the emergency operation centre for the elimination of polio virus and ebola virus disease in Nigeria was used. Field

Introduction: On March 17th, 2020, Oyo State recorded her first case of COVID-19 through a United Kingdom returnee. Oyo State Ministry of Health with the support of technical and development partners responded quickly and effectively to contain the outbreak. The outbreak was characterized by place, person and time.Methods: Field investigations were conducted and contact tracing and follow up done, all confirmed cases were identified, line-listed and analyzed using Epi-info version 7.Results: A total of 34confirmed cases were identified all within the capital city of Oyo State and two transferred from other states .The mean age was 49.1 ± 2.0 years with over 40% within the age group 50-59 years. There were 11(35.5%) health care workers infection. The case-fatality was 6.5%. The epidemic curve initially shows a typical propagated pattern, followed by a point source; though atypical.Conclusion: Outbreak of COVID-19 was confirmed in Oyo State. Field investigation provided information on the characteristics of persons, time and place. Intensified surveillance activities such as contact tracing and follow- up ,drive through testing and active case search were useful in early case detection and control of the outbreak