COVID-19 vaccine hesitancy among non-refugees and refugees in Kenya.

Factors associated with COVID-19 vaccine hesitancy (which we define as refusal to be vaccinated when asked, resulting in delayed or non- vaccination) are poorly studied in sub-Saharan Africa and among refugees, particularly in Kenya. Using survey data from wave five (March to June 2021) of the Kenya Rapid Response Phone Survey (RRPS), a household survey representative of the population of Kenya, we estimated the self-reported rates and factors associated with vaccine hesitancy among non-refugees and refugees in Kenya. Non-refugee households were recruited through sampling of the 2015/16 Kenya Household Budget Survey and random digit dialing. Refugee households were recruited through random sampling of registered refugees. Binary response questions on misinformation and information were transformed into a scale. We performed a weighted (to be representative of the overall population of Kenya) multivariable logistic regression including interactions for refugee status, with the main outcome being if the respondent self-reported that they would not take the COVID-19 vaccine if available at no cost. We calculated the marginal effects of the various factors in the model. The weighted univariate analysis estimated that 18.0% of non-refugees and 7.0% of refugees surveyed in Kenya would not take the COVID-19 vaccine if offered at no cost. Adjusted, refugee status was associated with a -13.1[95%CI:-17.5,-8.7] percentage point difference (ppd) in vaccine hesitancy. For the both refugees and non-refugees, having education beyond the primary level, having symptoms of COVID-19, avoiding handshakes, and washing hands more often were also associated with a reduction in vaccine hesitancy. Also for both, having used the internet in the past three months was associated with a 8.1[1.4,14.7] ppd increase in vaccine hesitancy; and disagreeing that the government could be trusted in responding to COVID-19 was associated with a 25.9[14.2,37.5]ppd increase in vaccine hesitancy. There were significant interactions between refugee status and some variables (geography, food security, trust in the Kenyan government's response to COVID-19, knowing somebody with COVID-19, internet use, and TV ownership). These relationships between refugee status and certain variables suggest that programming between refugees and non-refugees be differentiated and specific to the contextual needs of each group.

COVID-19 vaccine hesitancy among non-refugees and refugees in Kenya

Factors associated with COVID-19 vaccine hesitancy (which we define as refusal to be vaccinated when asked, resulting in delayed or non- vaccination) are poorly studied in sub-Saharan Africa and among refugees, particularly in Kenya. Using survey data from wave five (March to June 2021) of the Kenya Rapid Response Phone Survey (RRPS), a household survey representative of the population of Kenya, we estimated the self-reported rates and factors associated with vaccine hesitancy among non-refugees and refugees in Kenya. Non-refugee households were recruited through sampling of the 2015/16 Kenya Household Budget Survey and random digit dialing. Refugee households were recruited through random sampling of registered refugees. Binary response questions on misinformation and information were transformed into a scale. We performed a weighted (to be representative of the overall population of Kenya) multivariable logistic regression including interactions for refugee status, with the main outcome being if the respondent self-reported that they would not take the COVID-19 vaccine if available at no cost. We calculated the marginal effects of the various factors in the model. The weighted univariate analysis estimated that 18.0% of non-refugees and 7.0% of refugees surveyed in Kenya would not take the COVID-19 vaccine if offered at no cost. Adjusted, refugee status was associated with a -13.1[95%CI:-17.5,-8.7] percentage point difference (ppd) in vaccine hesitancy. For the both refugees and non-refugees, having education beyond the primary level, having symptoms of COVID-19, avoiding handshakes, and washing hands more often were also associated with a reduction in vaccine hesitancy. Also for both, having used the internet in the past three months was associated with a 8.1[1.4,14.7] ppd increase in vaccine hesitancy;and disagreeing that the government could be trusted in responding to COVID-19 was associated with a 25.9[14.2,37.5]ppd increase in vaccine hesitancy. There were significant interactions between refugee status and some variables (geography, food security, trust in the Kenyan government's response to COVID-19, knowing somebody with COVID-19, internet use, and TV ownership). These relationships between refugee status and certain variables suggest that programming between refugees and non-refugees be differentiated and specific to the contextual needs of each group.

COVID-19 vaccination refusal trends in Kenya over 2021.

BACKGROUND: Vaccination refusal exacerbates global COVID-19 vaccination inequities. No studies in East Africa have examined temporal trends in vaccination refusal, precluding addressing refusal. We assessed vaccine refusal over time in Kenya, and characterized factors associated with changes in vaccination refusal. METHODS: We analyzed data from the Kenya Rapid Response Phone Survey (RRPS), a household cohort survey representative of the Kenyan population including refugees. Vaccination refusal (defined as the respondent stating they would not receive the vaccine if offered to them at no cost) was measured in February and October 2021. Proportions of vaccination refusal were plotted over time. We analyzed factors in vaccination refusal using a weighted multivariable logistic regression including interactions for time. FINDINGS: Among 11,569 households, vaccination refusal in Kenya decreased from 24 % in February 2021 to 9 % in October 2021. Vaccination refusal was associated with having education beyond the primary level (-4.1[-0.7,-8.9] percentage point difference (ppd)); living with somebody who had symptoms of COVID-19 in the past 14 days (-13.72[-8.9,-18.6]ppd); having symptoms of COVID-19 in the past 14 days (11.0[5.1,16.9]ppd); and distrusting the government in responding to COVID-19 (14.7[7.1,22.4]ppd). There were significant interactions with time and: refugee status and geography, living with somebody with symptoms of COVID-19, having symptoms of COVID-19, and believing in misinformation. INTERPRETATION: The temporal reduction in vaccination refusal in Kenya likely represents substantial strides by the Kenyan vaccination program and possible learnt lessons which require examination. Going forward, there are still several groups which need specific targeting to decrease vaccination refusal and improve vaccination equity, including those with lower levels of education, those with recent COVID-19 symptoms, those who do not practice personal COVID-19 mitigation measures, refugees in urban settings, and those who do not trust the government. Policy and program should focus on decreasing vaccination refusal in these populations, and research focus on understanding barriers and motivators for vaccination.

COVID-19 vaccination and mask wearing behaviors in the United States, August 2020 - June 2021.

BACKGROUND: During the rollout of COVID-19 vaccination, many states relaxed mask wearing guidance for those vaccinated. The aim of this study was to examine the association between vaccination status and mask wearing behaviors. METHODS: Seven waves of surveys (n = 6721) were conducted between August 2020 and June 2021. Participants were asked about initiation of COVID-19 vaccination and mask wearing behavior at work/school or a grocery store. Odds ratios (ORs) and 95% confidence intervals (CIs) from logistic regression were used to estimate associations between vaccination status and mask wearing at work/school and at the grocery store. RESULTS: Between April and June 2021, mask wearing at work or school declined among both those vaccinated (74% to 49%) and unvaccinated (46% to 35%). There was a similar decline for mask wearing at grocery stores. The odds of wearing a mask were 2.35 times higher at work/school (95% CI: 1.82, 3.04) and 1.65 times at a grocery store (95% CI: 1.29, 2.11) among the vaccinated compared to unvaccinated. CONCLUSION: Mask wearing decreased after mask guidelines were relaxed, with consistently lower mask wearing among the unvaccinated, indicating a reluctance among the unvaccinated to adopt COVID-19 risk reduction behaviors.

Vaccine Hesitancy During the COVID-19 Pandemic: A Latent Class Analysis of Middle-Aged and Older US Adults.

It is important to distinguish between apprehensions that lead to vaccine rejection and those that do not. In this study, we (1) identifed latent classes of individuals by vaccination attitudes, and (2) compared classes of individuals by sociodemographic characteristics COVID-19 vaccination, and risk reduction behaviors. The COVID-19 Coping Study is a longitudinal cohort of US adults aged ≥ 55 years (n = 2358). We categorized individuals into three classes based on the adult Vaccine Hesitancy Scale using latent class analysis (LCA). The associations between class membership and sociodemographic characteristics, COVID-19 vaccination, and other behaviors were assessed using chi-square tests. In total, 88.9% were Vaccine Acceptors, 8.6% were Vaccine Ambivalent, and 2.5% Vaccine Rejectors. At the end, 90.7% of Acceptors, 62.4% of the Ambivalent, and 30.7% of the Rejectors had been vaccinated. The Ambivalent were more likely to be Black or Hispanic, and adopted social distancing and mask wearing behaviors intermediate to that of the Acceptors and Rejectors. Targeting the Vaccine Ambivalent may be an efficient way of increasing vaccination coverage. Controlling the spread of disease during a pandemic requires tailoring vaccine messaging to their concerns, e.g., through working with trusted community leaders, while promoting other risk reduction behaviors.

COVID-19 vaccine coverage, concerns, and preferences among Chinese ICU clinicians: a nationwide online survey.

BACKGROUND: Clinicians in intensive care units (ICUs) have been prioritized for COVID-19 vaccination. We aim to understand the reasons behind vaccination refusal, and assess preferences for COVID-19 vaccines among Chinese ICU clinicians. RESEARCH DESIGN AND METHODS: ICU clinicians throughout China's mainland were contacted to participate in an online survey. We compared concerns with vaccination status, and through a discrete choice experiment (DCE) assessed preferences for vaccines in terms of effectiveness, risk of adverse reactions, duration of immunity, and whether coworkers have been vaccinated. RESULTS: Among 11,951 ICU respondents from 252 prefecture-level regions, vaccination coverage was 75.4%, with an additional 9.2% not vaccinated but intending to, and 16.1% not vaccinated and not intending to. ICU clinicians not intending to be vaccinated significantly expressed more concerns about the speed of vaccine development (30.1%) and adverse reactions (65.9%). In the DCE, the only significant difference in preferences of a COVID-19 vaccine was for safety, with those not intending to have a stronger preference for a vaccine with fewer adverse reactions (OR = 4.49), compared to those already vaccinated (OR = 2.90) or those intending to vaccinate (OR = 3.46). CONCLUSION: Increasing vaccination coverage among Chinese ICU clinicians will require strong norms surrounding vaccination and transparency about safety information.

Effect of vaccine effectiveness and safety on COVID-19 vaccine acceptance in Detroit, Michigan, July 2020.

This study examined whether future COVID-19 vaccine acceptance differed based on an experimental manipulation of the vaccine safety and effectiveness profile. Data come from the Detroit Metro Area Community Study, a population-based study conducted July 15-20, 2020. Participants were asked whether they would get a new COVID-19 vaccine after being randomly assigned information about the vaccine's effectiveness (50% or 95%) and chance of fever (5% or 20%). Among 1,117 Detroiters, 51.3% would accept a COVID-19 vaccine that is 50% effective and 77.1% would accept a vaccine that is 95% effective. Women and adults ≥65 were more accepting of a vaccine; Black Detroiters were less accepting. Believing vaccines to be important, effective, and safe was associated with higher acceptance. Uptake of a COVID-19 may be limited, depending on perceived vaccine effectiveness and general attitudes toward vaccines. Public health approaches to modifying these attitudes will be especially important in the Black community.

A Bayesian Mixture Model for Predicting the COVID-19 Related Mortality in the United States.

An outbreak of SARS-CoV-2 has led to a global pandemic affecting virtually every country. As of August 31, 2020, globally, there have been approximately 25,500,000 confirmed cases and 850,000 deaths; in the United States (50 states plus District of Columbia), there have been more than 6,000,000 confirmed cases and 183,000 deaths. We propose a Bayesian mixture model to predict and monitor COVID-19 mortality across the United States. The model captures skewed unimodal (prolonged recovery) or multimodal (multiple surges) curves. The results show that across all states, the first peak dates of mortality varied between April 4, 2020 for Alaska and June 18, 2020 for Arkansas. As of August 31, 2020, 31 states had a clear bimodal curve showing a strong second surge. The peak date for a second surge ranged from July 1, 2020 for Virginia to September 12, 2020 for Hawaii. The first peak for the United States occurred about April 16, 2020-dominated by New York and New Jersey-and a second peak on August 6, 2020-dominated by California, Texas, and Florida. Reliable models for predicting the COVID-19 pandemic are essential to informing resource allocation and intervention strategies. A Bayesian mixture model was able to more accurately predict the shape of the mortality curves across the United States than other models, including the timing of multiple peaks. However, given the dynamic nature of the pandemic, it is important that the results be updated regularly to identify and better monitor future waves, and characterize the epidemiology of the pandemic.

Fine-scale spatial clustering of measles nonvaccination that increases outbreak potential is obscured by aggregated reporting data.

The United States experienced historically high numbers of measles cases in 2019, despite achieving national measles vaccination rates above the World Health Organization recommendation of 95% coverage with two doses. Since the COVID-19 pandemic began, resulting in suspension of many clinical preventive services, pediatric vaccination rates in the United States have fallen precipitously, dramatically increasing risk of measles resurgence. Previous research has shown that measles outbreaks in high-coverage contexts are driven by spatial clustering of nonvaccination, which decreases local immunity below the herd immunity threshold. However, little is known about how to best conduct surveillance and target interventions to detect and address these high-risk areas, and most vaccination data are reported at the state-level-a resolution too coarse to detect community-level clustering of nonvaccination characteristic of recent outbreaks. In this paper, we perform a series of computational experiments to assess the impact of clustered nonvaccination on outbreak potential and magnitude of bias in predicting disease risk posed by measuring vaccination rates at coarse spatial scales. We find that, when nonvaccination is locally clustered, reporting aggregate data at the state- or county-level can result in substantial underestimates of outbreak risk. The COVID-19 pandemic has shone a bright light on the weaknesses in US infectious disease surveillance and a broader gap in our understanding of how to best use detailed spatial data to interrupt and control infectious disease transmission. Our research clearly outlines that finer-scale vaccination data should be collected to prevent a return to endemic measles transmission in the United States.