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WCID 2024

Akumu Esther Joy

Akumu Esther Joy, Speaker at Infectious Diseases Conferences
Infectious Diseases Institute, Uganda
Title : Prospect of achieving a complete vaccination dosage during an outbreak: A secondary analysis of data from a high-frequency phone survey on COVID-19 conducted in Uganda


Background:  Coronavirus disease (COVID-19) was declared a pandemic by the World Health Organization (WHO) on 11th March 2020. COVID-19 vaccination is one of the strategies that was employed to contain COVID-19 infection. In Uganda, COVID-19 vaccination campaigns began in March 2021. Uganda has used a variety of vaccines including AstraZeneca, Johnson and Johnson, Moderna, Pfizer, Sinopharm, and Sinovac. By October 2023, Uganda had so far administered 32 million doses of COVID-19 with about 46.5% fully vaccinated of the 27 million eligible population. (CDC, Vaccine Administration based on Eligible Population, 2023). Vaccines are notably effective public health measures to mitigate the impact of epidemics and the effectiveness of vaccination depends on the uptake. In this analysis, we aimed to look at the likelihood of an individual having complete vaccination for the strategy that requires more than one vaccination shot.

Methods: A High-frequency phone survey on COVID-19 was conducted in Uganda by the Uganda Bureau of Statistics (UBOS) with support from the World Bank between 2020 and 2023. Data was downloaded from the World Bank online micro data library on 20th February 2023 (https://microdata.worldbank.org/index.php/catalog/3765/get-microdata). We used data from Round 9 which included data from 1871 households and 10636 individuals. For this analysis, we included participants who responded that they got a first shot of COVID-19 vaccination. We excluded those who responded that they did not get any shot of COVID-19 vaccination. At data analysis, participants' characteristics were summarized using frequencies and percentages for the categorical data, and medians and interquartile range for the continuous data.

During the survey, participants were asked about the number of vaccine doses received.  We estimated the likelihood of receiving a complete vaccination by calculating the proportion of participants who received the second COVID-19 vaccination shot among those who received the first COVID-19 vaccination shot. We compared the probability of receiving 2nd COVID-19 vaccine shot and the participants’ characteristics using the Chi-square test. To examine independent factors associated with the likelihood of receiving full vaccination, modified Poisson regression was employed because the outcome was common (i.e. prevalence of full vacation was >10%).

Aim: 1-To determine likelihood of getting a second vaccination shot

         2-To determine factors associated with getting a second vaccination shot

Results: Analysis was conducted on 9243 complete cases for participants: 4719 (51.1%) were female, with a median age of 16 years and inter-quartile range of 9-33 years, the majority (78.6%) were residing in rural areas. Nearly 3/4 (72.0%, 6657/9243) reported to have received a 2nd COVID-19 shot (prevalence of full vaccination 72.0%, 95%CI=71.1 – 72.9%).   The prevalence of getting the second vaccination COVID19 shot was higher among: the elderly (aged≥50) compared to younger ones  (76.2% vs 72.2%,70.4%,74.3% and 71.3% among 35-49,18-34,15-17,0-14 years respectively, P value=0.004), those who resided in the central region compared to other regions (82.4% vs. 59.6%, 74.4%, 72.9% for i.e.

Eastern, Northern and Western respectively, P value <0.000), individuals who considered health workers as their best-trusted source of information on vaccination compared to other sources of information (73.7% vs. 68.2%, 74.4% and 6865% for  i.e. Media, Government authorities and other sources respectively, P value<0.001), those who were somehow worried that a member of their immediate family might become seriously ill from COVID-19 compared to those who were not (77.6% vs. 65.7%,76.3% and 68.5%, for Very worried, Not too worried and Not worried at all respectively, P value=0.000), and those who considered COVID-19 virus outbreak as a substantial financial threat to their households compared those who did not (73.2% vs.72.1%, 71.4% and 52.8% for: moderate threat, Not much of a threat and Not a threat at all respectively, P value<0.000). At the adjusted analysis, old age (>50 years), residing in central region, source vaccination information, need to protect community’s health, fear of a family member getting ill, and fear of impact on household income, remained significantly associated (at 5% level) with willingness to get the second vaccination shot (prevalence ratios presented on Table 1).

Conclusion:  A high proportion of those who received the first vaccination shot were likely to go for another shot in order to achieve full vaccination. The likelihood of receiving full vaccination aligned with the groups of people whom the government of Uganda listed as priority group during the risk communication and prevention campaigns, and those who considered COVID-19 outbreak as a threat to their household finances. Risk and communication strategies targeting high risk groups is important for a successful implementation of vaccination strategy aimed to reduce the risk of fatal effects during disease outbreaks.


I am a statistician with extensive experience in working with routinely collected data from electronic medical records (EMR) and paper-based medical record systems. My specialization lies in pharmacovigilance (PV) projects, specifically in monitoring adverse drug reactions (ADRs) for people living with HIV. These projects were successfully conducted at regional referral hospitals across various regions in Uganda, sponsored by the US Centers for Disease Control and Prevention (CDC). As a result, I have acquired valuable expertise in managing data efficiently and leveraging the Redcap, Stata, Epidata, Powerbi, and Microsoft Excel for statistical analysis and data management. My career aspiration is to further my expertise in biostatistics, with a specialized focus on infectious diseases modeling, mapping, and the examination of exposures and their impact on disease outcomes.


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