Understanding COVID-19 vaccination behaviors and intentions in Ghana: A Behavioral Insights (BI) study.

INTRODUCTION: Vaccine uptake is influenced by a variety of factors. Behavioral Insights (BI) can be used to address vaccine hesitancy to understand the factors that influence the decision to take or refuse a vaccine. METHODOLOGY: This two-part study consisted of a survey designed to identify the influence of various drivers of people's COVID-19 vaccination status and their intention to take the vaccine in Ghana, as well as an experiment to test which of several behaviorally informed message frames had the greatest effect on vaccine acceptance. Data was collected from a total of 1494 participants; 1089 respondents (73%) reported already being vaccinated and 405 respondents (27%) reported not being vaccinated yet. The mobile phone-based surveys were conducted between December 2021 and January 2022 using Random Digit Dialing (RDD) to recruit study participants. Data analysis included regression models, relative weights analyses, and ANOVAs. RESULTS: The findings indicated that vaccine uptake in Ghana is influenced more by social factors (what others think) than by practical factors such as ease of vaccination. Respondents' perceptions of their family's and religious leaders' attitudes towards the vaccine were among the most influential drivers. Unexpectedly, healthcare providers' positive attitudes about the COVID-19 vaccine had a significant negative relationship with respondents' vaccination behavior. Vaccine intention was positively predicted by risk perception, ease of vaccination, and the degree to which respondents considered the vaccine effective. Perceptions of religious leaders' attitudes also significantly and positively predicted respondents' intention to get vaccinated. Although perceptions of religious leaders' views about the vaccine are an important driver of vaccine acceptance, results asking respondents to rank-order who influences them suggest that people may not be consciously aware-or do not want to admit-the degree to which they are affected by what religious leaders think. Message frames that included fear, altruism, social norms were all followed by positive responses toward the vaccine, as were messages with three distinct messengers: Ghana Health Services, a doctor, and religious leaders. CONCLUSIONS: What drives COVID-19 vaccine intentions does not necessarily drive behaviors. The results of this study can be used to develop appropriate COVID-19 vaccine uptake strategies targeting the most important drivers of COVID-19 vaccine acceptance, using effective message frames.

Estimation of bed net coverage indicators in Tanzania using mobile phone surveys: a comparison of sampling approaches.

BACKGROUND: Threats to maintaining high population access with effective bed nets persist due to errors in quantification, bed net wear and tear, and inefficiencies in distribution activities. Monitoring bed net coverage is therefore critical, but usually occurs every 2-3 years through expensive, large-scale household surveys. Mobile phone-based survey methodologies are emerging as an alternative to household surveys and can provide rapid estimates of coverage, however, little research on varied sampling approaches has been conducted in sub-Saharan Africa. METHODS: A nationally and regionally representative cross-sectional mobile phone survey was conducted in early 2021 in Tanzania with focus on bed net ownership and access. Half the target sample was contacted through a random digit dial methodology (n = 3500) and the remaining half was reached through a voluntary opt-in respondent pool (n = 3500). Both sampling approaches used an interactive voice response survey. Standard RBM-MERG bed net indicators and AAPOR call metrics were calculated. In addition, the results of the two sampling approaches were compared. RESULTS: Population access (i.e., the percent of the population that could sleep under a bed net, assuming one bed net per two people) varied from a regionally adjusted low of 48.1% (Katavi) to a high of 65.5% (Dodoma). The adjusted percent of households that had a least one bed net ranged from 54.8% (Pemba) to 75.5% (Dodoma); the adjusted percent of households with at least one bed net per 2 de facto household population ranged from 35.9% (Manyara) to 55.7% (Dodoma). The estimates produced by both sampling approaches were generally similar, differing by only a few percentage points. An analysis of differences between estimates generated from the two sampling approaches showed minimal bias when considering variation across the indicator for households with at least one bed net per two de facto household population. CONCLUSION: The results generated by this survey show that overall bed net access in the country appears to be lower than target thresholds. The results suggest that bed net distribution is needed in large sections of the country to ensure that coverage levels remain high enough to sustain protection against malaria for the population.