Floods in Sub-Saharan Africa; Causes, Determinants and Health Consequences.

Climate change has become a global issue and affects various regions at different levels. The hydro-climatic conditions and the natural fragility of Sub-Saharan Africa (SSA) make it prone to floods. The review was intended to comprehensively explore the determinants of floods in the continent and their effects on public health. An extensive systematic literature search in English was conducted for peer-reviewed papers, abstracts and internet articles, grey literature, and official Government documents and analysed to identify common themes, findings, and outcomes. Finally, the findings were categorized into common themes. The review revealed that the frequency and intensity of precipitations have increased in recent decades in SSA. This is worsened by anthropogenic activities including urban sprawl, population growth, and land use changes. The health effects of floods are diverse, varied, and specific to a particular context which can be immediate and long-term. The economic losses due to the flood events in the continent are huge. In conclusion, Governments across the continent need to give flood management a top priority as part of national disaster preparedness, response, and mitigation. Floods cannot be managed in isolation; it has to be incorporated into national urban planning with urbanization to make cities resilient and sustainable.

Epidemiological comparison of the first and second waves of the COVID-19 pandemic in Nigeria, February 2020-April 2021.

BACKGROUND: With reports of surges in COVID-19 case numbers across over 50 countries, country-level epidemiological analysis is required to inform context-appropriate response strategies for containment and mitigation of the outbreak. We aimed to compare the epidemiological features of the first and second waves of COVID-19 in Nigeria. METHODS: We conducted a retrospective analysis of the Surveillance Outbreak Response Management and Analysis System data of the first and second epidemiological waves, which were between 27 February and 24 October 2020, and 25 October 2020 to 3 April 2021, respectively. Descriptive statistical measures including frequencies and percentages, test positivity rate (TPR), cumulative incidence (CI) and case fatality rates (CFRs) were compared. A p value of <0.05 was considered statistically significant. All statistical analyses were carried out in STATA V.13. RESULTS: There were 802 143 tests recorded during the study period (362 550 and 439 593 in the first and second waves, respectively). Of these, 66 121 (18.2%) and 91 644 (20.8%) tested positive in the first and second waves, respectively. There was a 21.3% increase in the number of tests conducted in the second wave with TPR increasing by 14.3%. CI during the first and second waves were 30.3/100 000 and 42.0/100 000 respectively. During the second wave, confirmed COVID-19 cases increased among females and people 30 years old or younger and decreased among urban residents and individuals with travel history within 14 days of sample collection (p value <0.001). Most confirmed cases were asymptomatic at diagnosis during both waves: 74.9% in the first wave; 79.7% in the second wave. CFR decreased during the second wave (0.7%) compared with the first wave (1.8%). CONCLUSION: Nigeria experienced a larger but less severe second wave of COVID-19. Continued implementation of public health and social measures is needed to mitigate the resurgence of another wave.

Assessing the capacity of symptom scores to predict COVID-19 positivity in Nigeria: a national derivation and validation cohort study.

OBJECTIVES: This study aimed to develop and validate a symptom prediction tool for COVID-19 test positivity in Nigeria. DESIGN: Predictive modelling study. SETTING: All Nigeria States and the Federal Capital Territory. PARTICIPANTS: A cohort of 43 221 individuals within the national COVID-19 surveillance dataset from 27 February to 27 August 2020. Complete dataset was randomly split into two equal halves: derivation and validation datasets. Using the derivation dataset (n=21 477), backward multivariable logistic regression approach was used to identify symptoms positively associated with COVID-19 positivity (by real-time PCR) in children (≤17 years), adults (18-64 years) and elderly (≥65 years) patients separately. OUTCOME MEASURES: Weighted statistical and clinical scores based on beta regression coefficients and clinicians' judgements, respectively. Using the validation dataset (n=21 744), area under the receiver operating characteristic curve (AUROC) values were used to assess the predictive capacity of individual symptoms, unweighted score and the two weighted scores. RESULTS: Overall, 27.6% of children (4415/15 988), 34.6% of adults (9154/26 441) and 40.0% of elderly (317/792) that had been tested were positive for COVID-19. Best individual symptom predictor of COVID-19 positivity was loss of smell in children (AUROC 0.56, 95% CI 0.55 to 0.56), either fever or cough in adults (AUROC 0.57, 95% CI 0.56 to 0.58) and difficulty in breathing in the elderly (AUROC 0.53, 95% CI 0.48 to 0.58) patients. In children, adults and the elderly patients, all scoring approaches showed similar predictive performance. CONCLUSIONS: The predictive capacity of various symptom scores for COVID-19 positivity was poor overall. However, the findings could serve as an advocacy tool for more investments in resources for capacity strengthening of molecular testing for COVID-19 in Nigeria.

Use of long-lasting insecticidal nets among women attending antenatal clinic at a tertiary hospital in Bayelsa State, Nigeria 2019.

BACKGROUND: Malaria in pregnancy remains a major contributor to maternal and infant morbidity and mortality despite scale up in interventions. Its prevention is one of the major interventions in reducing maternal and infant morbidity and mortality. The ownership, utilization and predictors of use of long-lasting insecticide-treated nets (LLINs) for malaria prevention among women attending antenatal clinic (ANC) at a tertiary hospital in Bayelsa State Nigeria was assessed. METHODS: A cross-sectional study of 297 women recruited through systematic sampling was carried out. Information on sociodemographic characteristics, ownership, source and utilization of LLINs, were collected with a pre-tested structured interviewer-administered questionnaire. The relationship between use of LLIN and sociodemographic characteristics was examined using chi square and logistic regression at 5% level of significance. RESULTS: The mean age of respondents was 28.8 ± 2.6 years. Most (59.2%) had tertiary education and were mainly (88.2%) urban dwellers. Two hundred and fifty (84.2%) owned LLINs, and 196 (78%) used LLIN the night prior to the interview. Almost half of the respondents purchased their LLINs. Those who purchased LLINs were 3 times more likely to have used it (OR: 3.13, 95% CI 1.62-6.04) compared to those that got it free. Those who were gainfully employed (OR: 3.16, 95% CI 1.59-6.29) and those who earned above the minimum wage (OR: 2.88, 95% CI 1.45-5.72) were 3 times more likely to have used LLIN in their index pregnancy. CONCLUSION: The use of LLIN as a preventive measure against malaria was relatively high among the participants in this study, though still below national target. The major factors determining the use of LLIN among these women were purchase of LLINs and being gainfully employed. It was recommended that efforts should be made to enforce the policy of free LLINs at ANC registration at the tertiary hospitals, as this would further drive up ownership and utilization rates.