COVID-19 vaccination uptake in remote areas-Evidence from a panel survey in Bangladesh.

BACKGROUND: Vaccination has proven to be an essential strategy in combating the COVID-19 pandemic. This study aims to discern the factors influencing both the intentions for and actual behavior regarding COVID-19 vaccination among remote, rural populations in Bangladesh. METHODS: The study utilized panel survey data comprising 1,698 randomly selected household heads. These are predominantly illiterate, of Muslim religion, middle-aged, and male, with agriculture or day labor as primary income source. They reside in 36 locations distributed along the whole 250 km length of the Jamuna River in Bangladesh. Data collection occurred through face-to-face and telephone interviews conducted between September 2021 and October 2022. Descriptive statistics and Ordinary Least Squares regression models were employed to assess influence factors for COVID-19 vaccination intentions and uptake. The analyses considered the constructs of the Health Belief Model alongside sociodemographic characteristics such as gender, age, religion, education, and income source. RESULTS: Survey respondents showed a notably high willingness to receive the COVID-19 vaccine promptly upon its availability. However, the effectiveness of the Health Belief Model in elucidating COVID-19 vaccination uptake was limited, except for its availability component. Older individuals, those with higher levels of education, and individuals employed in government or formal sector occupations were prompt in receiving the COVID-19 vaccine as it became available. Gender, religion, and the presence of dependents in the household did not exert a significant influence on vaccination uptake. CONCLUSIONS: The results indicate that a strong willingness to receive the COVID-19 vaccine correlated with an increased likelihood of vaccine uptake once it was available. These findings suggest that a widespread distribution of COVID-19 vaccines to low-income and remote areas could have served as a vital strategy in mitigating the COVID-19 pandemic.

Perceptions of environmental changes among a climate-vulnerable population from Bangladesh.

Effective climate change adaptation requires a thorough understanding of whether and how affected populations perceive climatic and environmental changes. Existing research has been inconclusive regarding the consistency of these perceptions compared to objective meteorological indicators. Moreover, no systematic comparison has been done for the perception of discrete environmental events such as floods or erosion. This study relies on novel panel survey data of approximately 1700 households residing along the Jamuna River in Bangladesh as well as on unique individual-level, satellite-based erosion data. It compares respondents' perceptions of environmental events, namely riverbank erosion, and three climate change indicators, specifically long-term temperature change and changes in precipitation during wet and dry seasons, to objective measurements using satellite imagery and climatic time-series data (CRU TS). I find that long-term temperature change is perceived more accurately than long-term changes in precipitation. Given that educational attainment and climate change literacy among the study population are low, this indicates that global temperature increases are felt even by remote populations who have never heard the term climate change. Erosion is strongly overestimated, especially by those respondents who had been personally affected by it. Since human behavior is guided by perceptions rather than objective data, this has important policy implications, underlining the importance of considering people's perceptions if the goal is to assist them in adapting to environmental changes. Supplementary Information: The online version contains supplementary material available at 10.1007/s10584-024-03678-6.

Can Citizen Science using social media inform sanitation planning?

Improving the sanitation situation in a community that relies on on-site sanitation requires information about the quantity and quality of faecal sludge (FS) produced. Existing tools for data collection about FS characteristics are either imprecise or very costly. As information and communication technologies are becoming more available in low-income countries, Citizen Science is becoming an option for the collection of sanitation data. This study used an online survey distributed via social media to predict FS characteristics (Total Solids (TS), Total Suspended Solids (TSS), Volatile Suspended Solids (VSS), Chemical Oxygen Demand (COD) and Sludge Volume Index (SVI)) at 40 households in Blantyre, Malawi. Furthermore, the study investigated whether and how an online survey could yield cost-effective and representative information about the sanitation situation at the household level. Facebook and WhatsApp both introduced a bias towards higher income households as low-income households still lack access to smartphones and internet. WhatsApp (€1.01/reply) was significantly cheaper than Facebook (€3.00/reply) and conventional data generation with household interviewers (€1.47-2.20/reply). Monetary incentives generated more replies than pure social messaging. TSS, VSS and COD were significantly correlated to TS. The slope of the regression line of COD to TS (0.97) was similar to one reported for Uganda (0.88), suggesting that the ratio of COD to TS might be independent of the location. Statistically significant median differences of TS concentrations were found for the survey parameters "system type" and "solid waste", making these parameters candidates for predictors of FS characteristics. The sample size was too small for the other survey parameters to detect any differences statistically. Overall, using social media in a Citizen Science approach appears to be a promising new tool for FS characterization. In the current form, it can probably not replace other data collection tools, but rather complement them as a cost-efficient method to gain an initial assessment. Besides sanitation planning, social media and the Citizen Science approach could be employed for data collection in various fields of development cooperation.