Estimation of COVID-19 vaccine effectiveness against infections and severe outcomes using routine surveillance data in Kosovo, July-September 2021.

BACKGROUND: COVID-19 vaccines have proven effective against severe outcomes in many settings, yet vaccine effectiveness (VE) estimates remain lacking for Kosovo. We aimed to estimate VE against COVID-19 infections, hospitalisations, and deaths for one and two vaccine doses during the fourth pandemic wave in July-September 2021, the period when vaccination initially became widely available. METHODS: We analysed routine surveillance data to define cases and vaccination status as partially (one dose) or completely (two doses) vaccinated. We used the screening method to calculate the proportion of cases with the outcomes vaccinated (PCV). The proportion of the population vaccinated (PPV) was based on numbers vaccinated and the Kosovo population estimate on 30/09/2021. RESULTS: Between July-September 2021, 51,804 COVID-19 cases were reported in Kosovo with 9.3% of cases partially and 3.4% completely vaccinated. Estimated vaccine effectiveness for one dose was 93.1% (95%CI:92.9-93.2%) for infections, 90.3% (95%CI:88.8-91.7%) for hospitalisations, and 90.3% (95%CI:88.4-92.1%) for deaths. Estimated vaccine effectiveness for two doses was 97.8% (95%CI:97.6-97.9%) for infections, 94.5% (95%CI:93.3-95.6%) for hospitalisations, and 94.2% (95%CI: 93.7-96.5%) for deaths. CONCLUSIONS: This study provides real-world evidence for COVID-19 vaccine effectiveness in Kosovo using routine administrative data sources and the screening method. COVID-19 vaccine effectiveness against infections and severe outcomes in Kosovo was higher with two vaccine doses than one dose, which is in accordance with findings from other study designs and settings. Using the screening method in our study reflects an important initial methodology for estimating vaccine effectiveness with routine surveillance that may be particularly important for low- and middle-income settings with less robust surveillance systems or fewer opportunities to conduct more robust vaccine effectiveness study designs.

Methodological issues of retrospective surveys for measuring mortality of highly clustered diseases: case study of the 2014-16 Ebola outbreak in Bo District, Sierra Leone.

BACKGROUND: There is a lack of empirical data on design effects (DEFF) for mortality rate for highly clustered data such as with Ebola virus disease (EVD), along with a lack of documentation of methodological limitations and operational utility of mortality estimated from cluster-sampled studies when the DEFF is high. OBJECTIVES: The objectives of this paper are to report EVD mortality rate and DEFF estimates, and discuss the methodological limitations of cluster surveys when data are highly clustered such as during an EVD outbreak. METHODS: We analysed the outputs of two independent population-based surveys conducted at the end of the 2014-2016 EVD outbreak in Bo District, Sierra Leone, in urban and rural areas. In each area, 35 clusters of 14 households were selected with probability proportional to population size. We collected information on morbidity, mortality and changes in household composition during the recall period (May 2014 to April 2015). Rates were calculated for all-cause, all-age, under-5 and EVD-specific mortality, respectively, by areas and overall. Crude and adjusted mortality rates were estimated using Poisson regression, accounting for the surveys sample weights and the clustered design. RESULTS: Overall 980 households and 6,522 individuals participated in both surveys. A total of 64 deaths were reported, of which 20 were attributed to EVD. The crude and EVD-specific mortality rates were 0.35/10,000 person-days (95%CI: 0.23-0.52) and 0.12/10,000 person-days (95%CI: 0.05-0.32), respectively. The DEFF for EVD mortality was 5.53, and for non-EVD mortality, it was 1.53. DEFF for EVD-specific mortality was 6.18 in the rural area and 0.58 in the urban area. DEFF for non-EVD-specific mortality was 1.87 in the rural area and 0.44 in the urban area. CONCLUSION: Our findings demonstrate a high degree of clustering; this contributed to imprecise mortality estimates, which have limited utility when assessing the impact of disease. We provide DEFF estimates that can inform future cluster surveys and discuss design improvements to mitigate the limitations of surveys for highly clustered data.

Main findings: For humanitarian organizations it is imperative to document the methodological limitations of cluster surveys and discuss the utility.Added knowledge: This paper adds new knowledge on cluster surveys for highly clustered data such us in Ebola virus disease.Global health impact of policy and action: We provided empirical estimates and discuss design improvements to inform future study.