Influences of community engagement and health system strengthening for cholera control in cholera reporting countries.

The 2030 Global Task Force on Cholera Control Roadmap hinges on strengthening the implementation of multistranded cholera interventions, including community engagement and health system strengthening. However, a composite picture of specific facilitators and barriers for these interventions and any overlapping factors existing between the two, is lacking. Therefore, this study aims to address this shortcoming, focusing on cholera-reporting countries, which are disproportionately affected by cholera and may be cholera endemic. A scoping methodology was chosen to allow for iterative mapping, synthesis of the available research and to pinpoint research activity for global and local cholera policy-makers and shareholders. Using the Arksey and O'Malley framework for scoping reviews, we searched PubMed, Web of Science and CINAHL. Inclusion criteria included publication in English between 1990 and 2021 and cholera as the primary document focus in an epidemic or endemic setting. Data charting was completed through narrative descriptive and thematic analysis. Forty-four documents were included, with half relating to sub-Saharan African countries, 68% (30/44) to cholera endemic settings and 21% (9/44) to insecure settings. We identified four themes of facilitators and barriers to health systems strengthening: health system cooperation and agreement with external actors; maintaining functional capacity in the face of change; good governance, focused political will and sociopolitical influences on the cholera response and insecurity and targeted destruction. Community engagement had two themes: trust building in the health system and growing social cohesion. Insecurity and the community; cooperation and agreement; and sociopolitical influences on trust building were themes of factors acting at the interface between community engagement and health system. Given the decisive role of the community-health system interface for both sustained health system strengthening and community engagement, there is a need to advocate for conflict resolution, trust building and good governance for long-term cholera prevention and control in cholera reporting countries.

Public risk perception and behaviours towards COVID-19 during the first and second waves in Nigeria: a secondary data analysis.

OBJECTIVES: To describe changes in public risk perception and risky behaviours during the first wave (W1) and second wave (W2) of COVID-19 in Nigeria, associated factors and observed trend of the outbreak. DESIGN: A secondary data analysis of cross-sectional telephone-based surveys conducted during the W1 and W2 of COVID-19 in Nigeria. SETTING: Nigeria. PARTICIPANTS: Data from participants randomly selected from all states in Nigeria. PRIMARY OUTCOME: Risk perception for COVID-19 infection categorised as risk perceived and risk not perceived. SECONDARY OUTCOME: Compliance to public health and social measures (PHSMs) categorised as compliant; non-compliant and indifferent. ANALYSIS: Comparison of frequencies during both waves using χ2 statistic to test for associations. Univariate and multivariate logistic regression analyses helped estimate the unadjusted and adjusted odds of risk perception of oneself contracting COVID-19. Level of statistical significance was set at p<0.05. RESULTS: Triangulated datasets had a total of 6401 respondents, majority (49.5%) aged 25-35 years. Overall, 55.4% and 56.1% perceived themselves to be at risk of COVID-19 infection during the W1 and W2, respectively. A higher proportion of males than females perceived themselves to be at risk during the W1 (60.3% vs 50.3%, p<0.001) and the W2 (58.3% vs 52.6%, p<0.05). Residing in the south-west was associated with not perceiving oneself at risk of COVID-19 infection (W1-AOdds Ratio (AOR) 0.28; 95% CI 0.20 to 0.40; W2-AOR 0.71; 95% CI 0.52 to 0.97). There was significant increase in non-compliance to PHSMs in the W2 compared with W1. Non-compliance rate was higher among individuals who perceived themselves not to be at risk of getting infected (p<0.001). CONCLUSION: Risk communication and community engagement geared towards increasing risk perception of COVID-19 should be implemented, particularly among the identified population groups. This could increase adherence to PHSMs and potentially reduce the burden of COVID-19 in Nigeria.

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.

Patient characteristics associated with COVID-19 positivity and fatality in Nigeria: retrospective cohort study.

OBJECTIVE: Despite the increasing disease burden, there is a dearth of context-specific evidence on the risk factors for COVID-19 positivity and subsequent death in Nigeria. Thus, the study objective was to identify context-specific factors associated with testing positive for COVID-19 and fatality in Nigeria. DESIGN: Retrospective cohort study. SETTING: COVID-19 surveillance and laboratory centres in 36 states and the Federal Capital Territory reporting data to the Nigeria Centre for Disease Control. PARTICIPANTS: Individuals who were investigated for SARS-CoV-2 using real-time PCR testing during the study period 27 February-8 June 2020. METHODS: COVID-19 positivity and subsequent mortality. Multivariable logistic regression analyses were performed to identify factors independently associated with both outcome variables, and findings are presented as adjusted ORs (aORs) and 95% CIs. RESULTS: A total of 36 496 patients were tested for COVID-19, with 10 517 confirmed cases. Of 3215 confirmed cases with available clinical outcomes, 295 died. Factors independently associated with COVID-19 positivity were older age (p value for trend<0.0001), male sex (aOR 1.11, 95% CI 1.04 to 1.18) and the following presenting symptoms: cough (aOR 1.23, 95% CI 1.13 to 1.32), fever (aOR 1.45, 95% CI 1.45 to 1.71), loss of smell (aOR 7.78, 95% CI 5.19 to 11.66) and loss of taste (aOR 2.50, 95% CI 1.60 to 3.90). An increased risk of mortality following COVID-19 was observed in those aged ≥51 years, patients in farming occupation (aOR 7.56, 95% CI 1.70 to 33.53) and those presenting with cough (aOR 2.06, 95% CI 1.41 to 3.01), breathing difficulties (aOR 5.68, 95% CI 3.77 to 8.58) and vomiting (aOR 2.54, 95% CI 1.33 to 4.84). CONCLUSION: The significant risk factors associated with COVID-19 positivity and subsequent mortality in the Nigerian population are similar to those reported in studies from other countries and should guide clinical decisions for COVID-19 testing and specialist care referrals.

What are the drivers of recurrent cholera transmission in Nigeria? Evidence from a scoping review.

BACKGROUND: The 2018 cholera outbreak in Nigeria affected over half of the states in the country, and was characterised by high attack and case fatality rates. The country continues to record cholera cases and related deaths to date. However, there is a dearth of evidence on context-specific drivers and their operational mechanisms in mediating recurrent cholera transmission in Nigeria. This study therefore aimed to fill this important research gap, with a view to informing the design and implementation of appropriate preventive and control measures. METHODS: Four bibliographic literature sources (CINAHL (Plus with full text), Web of Science, Google Scholar and PubMed), and one journal (African Journals Online) were searched to retrieve documents relating to cholera transmission in Nigeria. Titles and abstracts of the identified documents were screened according to a predefined study protocol. Data extraction and bibliometric analysis of all eligible documents were conducted, which was followed by thematic and systematic analyses. RESULTS: Forty-five documents met the inclusion criteria and were included in the final analysis. The majority of the documents were peer-reviewed journal articles (89%) and conducted predominantly in the context of cholera epidemics (64%). The narrative analysis indicates that social, biological, environmental and climatic, health systems, and a combination of two or more factors appear to drive cholera transmission in Nigeria. Regarding operational dynamics, a substantial number of the identified drivers appear to be functionally interdependent of each other. CONCLUSION: The drivers of recurring cholera transmission in Nigeria are diverse but functionally interdependent; thus, underlining the importance of adopting a multi-sectoral approach for cholera prevention and control.

Identifying and quantifying the factors associated with cholera-related death during the 2018 outbreak in Nigeria.

INTRODUCTION: cholera outbreaks in Nigeria are often associated with high case fatality rates; however, there is a dearth of evidence on context-specific factors associated with the trend. This study therefore aimed to identify and quantify the factors associated with cholera-related deaths in Nigeria. METHODS: using a cross-sectional design, we analysed surveillance data from all the States that reported cholera cases during the 2018 outbreak, and defined cholera-related death as death of an individual classified as having cholera according to the Nigeria Centre for Disease Control case definition. Factors associated with cholera-related death were assessed using multivariable logistic regression and findings presented as adjusted odds ratios (ORs) with 95% Confidence Intervals (95% CIs). RESULTS: between January 1 and November 19, 2018, 41,394 cholera cases were reported across 20 States, including 815 cholera-related deaths. In the adjusted multivariable model, older age, male gender, living in peri-urban areas or in flooded states, infection during the rainy season, and delay in seeking health care by >2 days were positively associated with cholera-related death; whereas living in urban areas, hospitalisation in the course of illness, and presentation to a secondary hospital were negatively associated with cholera-related death. CONCLUSION: cholera-related deaths during the 2018 outbreak in Nigeria appeared to be driven by multiple factors, which further reemphasises the importance of adopting a multisectoral approach to the design and implementation of context-specific interventions in Nigeria.

Descriptive epidemiology of cholera outbreak in Nigeria, January-November, 2018: implications for the global roadmap strategy.

BACKGROUND: The cholera outbreak in 2018 in Nigeria reaffirms its public health threat to the country. Evidence on the current epidemiology of cholera required for the design and implementation of appropriate interventions towards attaining the global roadmap strategic goals for cholera elimination however seems lacking. Thus, this study aimed at addressing this gap by describing the epidemiology of the 2018 cholera outbreak in Nigeria. METHODS: This was a retrospective analysis of surveillance data collected between January 1st and November 19th, 2018. A cholera case was defined as an individual aged 2 years or older presenting with acute watery diarrhoea and severe dehydration or dying from acute watery diarrhoea. Descriptive analyses were performed and presented with respect to person, time and place using appropriate statistics. RESULTS: There were 43,996 cholera cases and 836 cholera deaths across 20 states in Nigeria during the outbreak period, with an attack rate (AR) of 127.43/100,000 population and a case fatality rate (CFR) of 1.90%. Individuals aged 15 years or older (47.76%) were the most affected age group, but the proportion of affected males and females was about the same (49.00 and 51.00% respectively). The outbreak was characterised by four distinct epidemic waves, with higher number of deaths recorded in the third and fourth waves. States from the north-west and north-east regions of the country recorded the highest ARs while those from the north-central recorded the highest CFRs. CONCLUSION: The severity and wide-geographical distribution of cholera cases and deaths during the 2018 outbreak are indicative of an elevated burden, which was more notable in the northern region of the country. Overall, the findings reaffirm the strategic role of a multi-sectoral approach in the design and implementation of public health interventions aimed at preventing and controlling cholera in Nigeria.