Epidemiological description of and response to a large yellow fever outbreak in Edo state Nigeria, September 2018 - January 2019.

BACKGROUND: Edo State Surveillance Unit observed the emergence of a disease with "no clear-cut-diagnosis", which affected peri-urban Local Government Areas (LGAs) from September 6 to November 1, 2018. On notification, the Nigeria Centre for Disease Control deployed a Rapid Response Team (RRT) to support outbreak investigation and response activities in the State. This study describes the epidemiology of and response to a large yellow fever (YF) outbreak in Edo State. METHODS: A cross-sectional descriptive outbreak investigation of YF outbreak in Edo State. A suspected case of YF was defined as "Any person residing in Edo State with acute onset of fever and jaundice appearing within 14 days of onset of the first symptoms from September 2018 to January 2019". Our response involved active case search in health facilities and communities, retrospective review of patients' records, rapid risk assessment, entomological survey, rapid YF vaccination coverage assessment, blood sample collection, case management and risk communication. Descriptive data analysis using percentages, proportions, frequencies were made. RESULTS: A total of 209 suspected cases were line-listed. Sixty-seven (67) confirmed in 12 LGAs with 15 deaths [Case fatality rate (CFR 22.4%)]. Among confirmed cases, median age was 24.8, (range 64 (1-64) years; Fifty-one (76.1%) were males; and only 13 (19.4%) had a history of YF vaccination. Vaccination coverage survey involving 241 children revealed low YF vaccine uptake, with 44.6% providing routine immunisation cards for sighting. Risk of YF transmission was 71.4%. Presence of Aedes with high-larval indices (House Index ≥5% and/or Breteau Index ≥20) were established in all the seven locations visited. YF reactive mass vaccination campaign was implemented. CONCLUSION: Edo State is one of the states in Nigeria with the highest burden of yellow fever. More males were affected among the confirmed. Major symptoms include fever, jaundice, weakness, and bleeding. Majority of surveillance performance indicators were above target. There is a high risk of transmission of the disease in the state. Low yellow fever vaccination coverage, and presence of yellow fever vectors (Ae.aegypti, Ae.albopictus and Ae.simpsoni) are responsible for cases in affected communities. Enhanced surveillance, improved laboratory sample management, reactive vaccination campaign, improved yellow fever case management and increased risk communication/awareness are very important mitigation strategies to be sustained in Edo state to prevent further spread and mortality from yellow fever.

Schistosomiasis Seroprevalence among Children Aged 0-14 Years in Nigeria, 2018.

The first nationally representative, population-based study of schistosomiasis seroprevalence in Nigeria was conducted using blood samples and risk-factor data collected during the 2018 Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS). Schistosomiasis seroprevalence was estimated by analyzing samples for reactivity to schistosome soluble egg antigen (SEA) in a multiplex bead assay; NAIIS survey data were assessed to identify potential risk factors for seropositivity. The SEA antibody data were available for 31,459 children aged 0 to 14 years. Overall seroprevalence was 17.2% (95% CI: 16.3-18.1%). Seropositive children were identified in every age group, including children < 5 years, and seroprevalence increased with increasing age (P < 0.0001). Several factors were associated with increased odds of seropositivity, including being a boy (odds ratio [OR] = 1.34, 95% CI: 1.24-1.45), living in a rural area (OR = 2.2, 95% CI: 1.9-2.5), and animal ownership (OR = 1.67, 95% CI: 1.52-1.85). Access to improved sanitation and drinking water sources were associated with decreased odds of seropositivity (OR = 0.52, 95% CI: 0.47-0.58 and OR = 0.53, 95% CI: 0.47-0.60, respectively) regardless of whether the child lived in a rural (sanitation: adjusted odds ratio [aOR] = 0.7, 95% CI: 0.6-0.8; drinking water: aOR = 0.7, 95% CI: 0.6-0.8) or urban area (sanitation: aOR = 0.6, 95% CI: 0.5-0.7; drinking water: aOR = 0.5, 95% CI: 0.4-0.6), highlighting the importance of these factors for schistosomiasis prevention and control. These results identified additional risk populations (children < 5 years) and a new risk factor (animal ownership) and could be used to monitor the impact of control programs.

Nationwide surveillance identifies yellow fever and chikungunya viruses transmitted by various species of Aedes mosquitoes in Nigeria.

Background: Since its reemergence in 2017, yellow fever (YF) has been active in Nigeria. The Nigeria Centre for Disease Control (NCDC) has coordinated responses to the outbreaks with the support of the World Health Organization (WHO). The National Arbovirus and Vectors Research Centre (NAVRC) handles the vector component of these responses. This study sought to identify the vectors driving YF transmission and any of the targeted arboviruses and their distribution across states. Methods: Eggs, larvae and pupae as well as adult mosquitoes were collected in observational, analytical, and cross-sectional surveys conducted in sixteen YF outbreak states between 2017 and 2020. Adult mosquitoes (field-collected or reared from immature stages) were morphologically identified, and arboviruses were detected using RT-qPCR at the African Centre of Excellence for Genomics of Infectious Diseases (ACEGID). Results: Aedes mosquitoes were collected in eleven of the sixteen states surveyed and the mosquitoes in nine states were found infected with arboviruses. A total of seven Aedes species were collected from different parts of the country. Aedes aegypti was the most dominant (51%) species, whereas Aedes africanus was the least (0.2%). Yellow fever virus (YFV) was discovered in 33 (~26%) out of the 127 Aedes mosquito pools. In addition to YFV, the Chikungunya virus (CHIKV) was found in nine pools. Except for Ae. africanus, all the Aedes species tested positive for at least one arbovirus. YFV-positive pools were found in six (6) Aedes species while CHIKV-positive pools were only recorded in two Aedes species. Edo State had the most positive pools (16), while Nasarawa, Imo, and Anambra states had the least (1 positive pool). Breteau and house indices were higher than normal transmission thresholds in all but one state. Conclusion: In Nigeria, there is a substantial risk of arbovirus transmission by Aedes mosquitoes, with YFV posing the largest threat at the moment. This risk is heightened by the fact that YFV and CHIKV have been detected in vectors across outbreak locations. Hence, there is an urgent need to step up arbovirus surveillance and control activities in the country.

Metagenomic sequencing characterizes a wide diversity of viruses in field mosquito samples in Nigeria.

Mosquito vectors are a tremendous public health threat. One in six diseases worldwide is vector-borne transmitted mainly by mosquitoes. In the last couple of years, there have been active Yellow fever virus (YFV) outbreaks in many settings in Nigeria, and nationwide, entomological surveillance has been a significant effort geared towards understanding these outbreaks. In this study, we used a metagenomic sequencing approach to characterize viruses present in vector samples collected during various outbreaks of Yellow fever (YF) in Nigeria between 2017 and 2020. Mosquito samples were grouped into pools of 1 to 50 mosquitoes, each based on species, sex and location. Twenty-five pools of Aedes spp and one pool of Anopheles spp collected from nine states were sequenced and metagenomic analysis was carried out. We identified a wide diversity of viruses belonging to various families in this sample set. Seven different viruses detected included: Fako virus, Phasi Charoen-like virus, Verdadero virus, Chaq like-virus, Aedes aegypti totivirus, cell fusing agent virus and Tesano Aedes virus. Although there are no reports of these viruses being pathogenic, they are an understudied group in the same families and closely related to known pathogenic arboviruses. Our study highlights the power of next generation sequencing in identifying Insect specific viruses (ISVs), and provide insight into mosquito vectors virome in Nigeria.

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.

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.

The response to re-emergence of yellow fever in Nigeria, 2017.

Yellow fever (YF) is an acute viral hemorrhagic disease caused by the YF virus (arbovirus) which continues to cause severe morbidity and mortality in Africa. A case of YF was confirmed in Nigeria on the 12th of September 2017, 21 years after the last confirmed case. The patient belongs to a nomadic population with a history of low YF vaccination uptake, in the Ifelodun Local Government Area (LGA) of Kwara State, Nigeria. An active case search in Ifelodun and its five contiguous LGAs led to the listing of 55 additional suspect cases of YF within the period of the outbreak investigation between September 18 to October 6, 2017. The median age of cases was 15 years, and 54.4% were males. Of these, blood samples were collected from 30 cases; nine tested positive in laboratories in Nigeria and six were confirmed positive for YF by the WHO reference laboratory in the region; Institut Pasteur, Dakar. A rapid YF vaccination coverage assessment was carried out, resulting in a coverage of 46% in the LGAs, with 25% of cases able to produce their vaccination cards. All stages of the yellow fever vector, Aedes mosquito were identified in the area, with high larval indices (House and Breteau) observed. In response to the outbreak, YF surveillance was intensified across all States in Nigeria, as well as reactive vaccination and social mobilisation campaigns carried out in the affected LGAs in Kwara State. A state-wide YF preventive campaign was also initiated.

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.

Reduced evolutionary rate in reemerged Ebola virus transmission chains.

On 29 June 2015, Liberia's respite from Ebola virus disease (EVD) was interrupted for the second time by a renewed outbreak ("flare-up") of seven confirmed cases. We demonstrate that, similar to the March 2015 flare-up associated with sexual transmission, this new flare-up was a reemergence of a Liberian transmission chain originating from a persistently infected source rather than a reintroduction from a reservoir or a neighboring country with active transmission. Although distinct, Ebola virus (EBOV) genomes from both flare-ups exhibit significantly low genetic divergence, indicating a reduced rate of EBOV evolution during persistent infection. Using this rate of change as a signature, we identified two additional EVD clusters that possibly arose from persistently infected sources. These findings highlight the risk of EVD flare-ups even after an outbreak is declared over.