COVID-19 Vaccine Acceptance and Hesitancy in Health Care Workers in Somalia: Findings from a Fragile Country with No Previous Experience of Mass Adult Immunization.

Coverage of COVID-19 vaccines in Somalia remains low, including among health workers. This study aimed to identify factors associated with COVID-19 vaccine hesitancy among health workers. In this cross-sectional, questionnaire-based study, 1476 health workers in government and private health facilities in Somalia's federal member states were interviewed face-to-face about their perceptions of and attitudes toward COVID-19 vaccines. Both vaccinated and unvaccinated health workers were included. Factors associated with vaccine hesitancy were evaluated in a multivariable logistic regression analysis. Participants were evenly distributed by sex, and their mean age was 34 (standard deviation 11.8) years. The overall prevalence of vaccine hesitancy was 38.2%. Of the 564 unvaccinated participants, 39.0% remained hesitant. The factors associated with vaccine hesitancy were: being a primary health care worker (adjusted odds ratio (aOR) = 2.37, 95% confidence interval (CI): 1.15-4.90) or a nurse (aOR = 2.12, 95% CI: 1.05-4.25); having a master's degree (aOR = 5.32, 95% CI: 1.28-22.23); living in Hirshabelle State (aOR = 3.23, 95% CI: 1.68-6.20); not having had COVID-19 (aOR = 1.96, 95% CI: 1.15-3.32); and having received no training on COVID-19 (aOR = 1.54, 95% CI: 1.02-2.32). Despite the availability of COVID-19 vaccines in Somalia, a large proportion of unvaccinated health workers remain hesitant about being vaccinated, potentially influencing the public's willingness to take the vaccine. This study provides vital information to inform future vaccination strategies to achieve optimal coverage.

Population-based sero-epidemiological investigation of SARS-CoV-2 infection in Somalia.

OBJECTIVES: To explore the burden of coronavirus disease 2019 (COVID-19) in Somalia by measuring the seroprevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the general population. METHODS: We recruited a convenience sample of 2751 participants from among individuals attending outpatient and inpatient departments of public health facilities, or their accompanying family members. Participants were interviewed to collect sociodemographic data and provided a blood sample. We calculated seropositivity rates overall and by sex, age group, state, residence, education and marital status. We used logistic regression analysis - odds ratios and 95% confidence intervals (CI) - to investigate sociodemographic correlates of seropositivity. RESULTS: The overall seropositivity rate was 56.4% (95% CI 54.5-58.3%), while 8.8% of participants reported being previously diagnosed with COVID-19 by July 2021. In the regression analysis, after controlling for covariates, urban residence was significantly asscoiated with seropositivity: OR = 1.74 (95% CI: 1.19-2.55). CONCLUSIONS: Our results show a high seroprevalence rate of SARS-CoV-2 in the Somali population (56.4%), and indicate that many infections have not been captured by the country's surveillance system resulting in considerable under-reporting.

Value of Verbal Autopsy in a Fragile Setting: Reported versus Estimated Community Deaths Associated with COVID-19, Banadir, Somalia.

BACKGROUND: Accurate mortality data associated with infectious diseases such as coronavirus disease 2019 (COVID-19) are often unavailable in countries with fragile health systems such as Somalia. We compared officially reported COVID-19 deaths in Somalia with COVID-19 deaths estimated using verbal autopsy. METHODS: We interviewed relatives of deceased persons to collect information on symptoms, cause, and place of death. We compared these data with officially reported data and estimated the positive and negative predictive values of verbal autopsy. RESULTS: We identified 530 deaths during March-October 2020. We classified 176 (33.2%) as probable COVID-19 deaths. Most deaths (78.5%; 416/530) occurred at home and 144 (34.6%) of these were attributed to COVID-19. The positive predictive value of verbal autopsy was lower for home deaths (22.3%; 95% CI: 15.7-30.1%) than for hospital deaths (32.3%; 95% CI: 16.7-51.4%). The negative predictive value was higher: 97.8% (95% CI: 95.0-99.3%) for home deaths and 98.4% (95% CI: 91.5-100%) for hospital deaths. Conclusions Verbal autopsy has acceptable predictive value to estimate COVID-19 deaths where disease prevalence is high and can provide data on the COVID-19 burden in countries with low testing and weak mortality surveillance where home deaths may be missed.

Evaluation of the electronic Early Warning and Response Network (EWARN) system in Somalia, 2017-2020.

BACKGROUND: In 2008, Somalia introduced an electronic based Early Warning Alert and Response Network (EWARN) for real time detection and response to alerts of epidemic prone diseases in a country experiencing a complex humanitarian situation. EWARN was deactivated between 2008 to 2016 due to civil conflict and reactivated in 2017 during severe drought during a cholera outbreak. We present an assessment of the performance of the EWARN in Somalia from January 2017 to December 2020, reflections on the successes and failures, and provide future perspectives for enhancement of the EWARN to effectively support an Integrated Disease Surveillance and Response strategy. METHODS: We described geographical coverage of the EWARN, system attributes, which included; sensitivity, flexibility, timeliness, data quality (measured by completeness), and positive predictive value (PPV). We tested for trends of timeliness of submission of epidemiological reports across the years using the Cochran-Mantel-Haenszel stratified test of association. RESULTS: By December 2020, all 6 states and the Banadir Administrative Region were implementing EWARN. In 2017, only 24.6% of the records were submitted on time, but by 2020, 96.8% of the reports were timely (p < 0.001). Completeness averaged < 60% in all the 4 years, with the worst-performing year being 2017. Overall, PPV was 14.1%. Over time, PPV improved from 7.1% in 2017 to 15.4% in 2019 but declined to 9.7% in 2020. Alert verification improved from 2.0% in 2017 to 52.6% by 2020, (p < 0.001). In 2020, EWARN was enhanced to facilitate COVID-19 reporting demonstrating its flexibility to accommodate the integration of reportable diseases. CONCLUSIONS: During the past 4 years of implementing EWARN in Somalia, the system has improved significantly in timeliness, disease alerts verification, and flexibility in responding to emerging disease outbreaks, and enhanced coverage. However, the system is not yet optimal due to incompleteness and lack of integration with other systems suggesting the need to build additional capacity for improved disease surveillance coverage, buttressed by system improvements to enhance data quality and integration.

Preliminary findings of COVID-19 infection in health workers in Somalia: A reason for concern.

BACKGROUND: Somalia, a country with a long history of instability, has a fragile healthcare system that is consistently understaffed. A large number of healthcare workers (HCWs) have become infected during the coronavirus disease-19 (COVID-19) pandemic. OBJECTIVE: This report presents the preliminary findings of COVID-19 infection in Somali HCWs, the first of such information from Somalia. METHODS: This preliminary retrospective study analysed available data on infection rates among Somali HCWs. RESULTS: As of 30 September 2020, 3700 cases of COVID-19, including 98 deaths, had been reported in Somalia; 191 (5%) of these cases were HCWs. During the first 180 days of the outbreak, 311 HCWs were tested for COVID-19 and 191 tested positive (positivity rate: 61%). During the epidemic's peak, HCWs represented at least 5% of cases. Of the 191 infected cases, 52 (27%) were doctors, 63 (33%) were nurses, seven (4%) were laboratory technicians, and 36% were other staff. CONCLUSION: More information must be sought to put measures in place to protect the health and safety of HCWs in Somalia's already understaffed and fragile healthcare system.