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Previous efforts to estimate the travel time to comprehensive emergency obstetric care (CEmOC) in low- and middle-income countries (LMICs) have either been based on spatial models or self-reported travel time, both with known inaccuracies. The study objectives were to estimate more realistic travel times for pregnant women in emergency situations using Google Maps, determine system-level factors that influence travel time and use these estimates to assess CEmOC geographical accessibility and coverage in Lagos state, Nigeria. Data on demographics, obstetric history and travel to CEmOC facilities of pregnant women with an obstetric emergency, who presented between 1st November 2018 and 31st December 2019 at a public CEmOC facility were collected from hospital records. Estimated travel times were individually extracted from Google Maps for the period of the day of travel. Bivariate and multivariate analyses were used to test associations between travel and health system-related factors with reaching the facility >60 minutes. Mean travel times were compared and geographical coverage mapped to identify 'hotspots' of predominantly >60 minutes travel to facilities. For the 4005 pregnant women with traceable journeys, travel time ranges were 2-240 minutes (without referral) and 7-320 minutes (with referral). Total travel time was within the 60 and 120 minute benchmark for 80 and 96% of women, respectively. The period of the day of travel and having been referred were significantly associated with travelling >60 minutes. Many pregnant women living in the central cities and remote towns typically travelled to CEmOC facilities around them. We identified four hotspots from which pregnant women travelled >60 minutes to facilities. Mean travel time and distance to reach tertiary referral hospitals were significantly higher than the secondary facilities. Our findings suggest that actions taken to address gaps need to be contextualized. Our approach provides a useful guide for stakeholders seeking to comprehensively explore geographical inequities in CEmOC access within urban/peri-urban LMIC settings. [ABSTRACT FROM AUTHOR]

Introduction: heightened surveillance of the severe acute respiratory syndrome coronavirus-2 (SARSCoV-2) 2019 outbreak in Wuhan, China activated several collaborative laboratory drills on its detection by health institutions in Nigeria. We hereby detail the laboratory detection and confirmation of the novel SARS-CoV-2 virus of the index case imported into Nigeria. Methods: viral RNA from sputum sample of the index case was tested for SARS-CoV-2 envelope (E) and RNA dependent RNA polymerase (RdRp) genes using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Genetic analysis using a partial sequence of RdRp gene was used for laboratory confirmation, evolutionary inferences, and relatedness to previous strains of betacorona viruses in Nigeria. Results: both qRT-PCR for the E and RdRp genes indicated the presence of the SARSCoV-2 RNA by showing cycle threshold (ct) values of 20.27 and 25.26 respectively. On successful completion of the sequencing run, data aligned with >98% similarity of the 2019 circulating strain of Coronavirus SARS-CoV-2. Evolutionary algorithms revealed that the sequence (RdRp gene) of the outbreak circulating strains were more conserved unlike previous coronavirus outbreaks. Data showed that some coronaviruses belonging to the BetaCoV genus had earlier been reported in bats and camels in Nigeria indicating the possibility of sero-protection in exposed populations. Conclusion: pre-laboratory drills prompted early diagnosis and confirmation of SARS-CoV-2 index case in Nigeria initiating rapid case-definition, contact tracing, and successful epidemiological management of the outbreak. Rapid sequencing of the viral genome during strategic points of the outbreak curve and making libraries of new variants for improved vaccine development are recommended. [ABSTRACT FROM AUTHOR]

• Cough, fever and difficulty in breathing were the most common COVID-19 symptoms. • Severity of symptoms at presentation was the most significant predictor of death. • Difficulty in breathing was the most significant symptom predictive of death. • The case fatality rate was 4.3%. Lagos state remains the epicentre of COVID-19 in Nigeria. We describe the symptoms and signs of the first 2,184 PCR-confirmed COVID-19 patients admitted at COVID-19 treatment centers in Lagos State. We also assessed the relationship between patients' presenting symptoms, sociodemographic and clinical characteristics and COVID-19 deaths.. Medical records of PCR-confirmed COVID-19 patients were extracted and analyzed for their symptoms, symptom severity, presence of comorbidities and outcome. The ages of the patients ranged from 4 days to 98 years with a mean of 43.0(16.0) years. Of the patients who presented with symptoms, cough (19.3%) was the most common presenting symptom. This was followed by fever (13.7%) and difficulty in breathing, (10.9%). The most significant clinical predictor of death was the severity of symptoms and signs at presentation. Difficulty in breathing was the most significant symptom predictor of COVID-19 death (OR:19.26 95% CI 10.95-33.88). The case fatality rate was 4.3%. Primary care physicians and COVID-19 frontline workers should maintain a high index of suspicion and prioritize the care of patients presenting with these symptoms. Community members should be educated on such predictors and ensure that patients with these symptoms seek care early to reduce the risk of deaths associated with COVID-19. [ABSTRACT FROM AUTHOR]