Calculation, knowledge, and identity: Dimensions of trust when making COVID-19 vaccination choices in China.

Vaccine hesitancy threatens the response to the COVID-19 pandemic and to other infectious disease outbreaks globally. Fostering trust has been highlighted as a critical factor in addressing vaccine hesitancy and expanding vaccine coverage, but qualitative exploration of trust in the context of vaccination remains limited. We contribute to filling this gap by providing a comprehensive qualitative analysis of trust in the context of COVID-19 vaccination in China. We conducted 40 in-depth interviews with Chinese adults in December 2020. During data collection, trust emerged as a highly salient topic. Interviews were audio-recorded, transcribed verbatim, translated into English, and analyzed with a combination of inductive and deductive coding. Following established trust literature, we differentiate between three types of trust - calculation-based trust, knowledge-based trust, and identity-based trust - which we grouped across components of the health system, as informed by the WHO's building blocks. Our results highlight how participants attributed their level of trust in COVID-19 vaccines to their trust in the medical technology itself (based on assessing risks and benefits or previous vaccination experiences), the service delivery and health workforce (informed by past experiences with health providers and their role throughout the pandemic), and leadership and governance (drawing on notions of government performance and patriotism). Reducing negative impact from past vaccine controversies, increasing the credibility of pharmaceutical companies, and fostering clear communication are identified as important channels for facilitating trust. Our findings emphasize a strong need for comprehensive information on COVID-19 vaccines and increased promotion of vaccination by credible figures.

Early-stage predictors of deterioration among 3145 nonsevere SARS-CoV-2-infected people community-isolated in Wuhan, China: A combination of machine learning algorithms and competing risk survival analyses.

OBJECTIVE: To determine which early-stage variables best predicted the deterioration of coronavirus disease 2019 (COVID-19) among community-isolated people infected with severe acute respiratory syndrome coronavirus 2 and to test the performance of prediction using only inexpensive-to-measure variables. METHODS: Medical records of 3145 people isolated in two Fangcang shelter hospitals (large-scale community isolation centers) from February to March 2020 were accessed. Two complementary methods-machine learning algorithms and competing risk survival analyses-were used to test potential predictors, including age, gender, severity upon admission, symptoms (general symptoms, respiratory symptoms, and gastrointestinal symptoms), computed tomography (CT) signs, and comorbid chronic diseases. All variables were measured upon (or shortly after) admission. The outcome was deterioration versus recovery of COVID-19. RESULTS: More than a quarter of the 3145 people did not present any symptoms, while one-third ended isolation due to deterioration. Machine learning models identified moderate severity upon admission, old age, and CT ground-glass opacity as the most important predictors of deterioration. Removing CT signs did not degrade the performance of models. Competing risk models identified age ≥ 35 years, male gender, moderate severity upon admission, cough, expectoration, CT patchy opacity, CT consolidation, comorbid diabetes, and comorbid cardiovascular or cerebrovascular diseases as significant predictors of deterioration, while a stuffy or runny nose as a predictor of recovery. CONCLUSIONS: Early-stage prediction of COVID-19 deterioration can be made with inexpensive-to-measure variables, such as demographic characteristics, severity upon admission, observable symptoms, and self-reported comorbid diseases, among asymptomatic people and mildly to moderately symptomatic patients.

Deliberation, context, emotion and trust - understanding the dynamics of adults' COVID-19 vaccination decisions in Germany.

BACKGROUND: Willingness to vaccinate against coronavirus disease 2019 (COVID-19), which is vital to successful vaccination campaigns, is wavering and suboptimal. In Germany, quantitative research highlighted concerns regarding the safety and efficacy of COVID-19 vaccines as barriers to uptake, but qualitative insights regarding individuals' decisions about COVID-19 vaccines and how personal perceptions reflect or refute existing behavioral theories are lacking. METHODS: To identify how individuals make COVID-19 vaccination decisions within real-life contexts, we conducted 33 semi-structured, in-depth qualitative interviews with individuals in Germany between March and April 2021 using maximum variation sampling, focusing on perceptions of COVID-19 vaccines. Analysis, informed by a framework approach, began in the field via debriefings and was amplified upon the conclusion of data collection. RESULTS: Four interconnected themes (deliberation, context, emotion, trust) shaped respondents' decisions about vaccination. Personal deliberation regarding benefits and risks of vaccines and perceptions of the broader social and political context sparked a spectrum of emotions that underpinned vaccination decisions. Trust in science and researchers emerged as a powerful protective factor facilitating the decision to get vaccinated even amidst a rapidly changing context and disconcerting information. CONCLUSIONS: Our findings add to ongoing debates about the breadth of vaccination decisions by highlighting how respondents are influenced by their perceptions of the political context and the emotional heft of their decisions. The role of cognitive evaluation, context, and emotions mirrors other decision-making frameworks, particularly the Risk as Feelings Theory. We extend on the elements of this theory by highlighting trust as a protective factor when making decisions particularly in highly uncertain contexts. Success of vaccination campaigns, more important than ever as new variants of COVID-19 emerge, is interwoven with an ability to bolster trust in science. Communicating public-health decisions and information about vaccines transparently without instilling fear offers promising chances to strengthen public trust in COVID-19 vaccines. TRIAL REGISTRATION: German Clinical Trials Register ( DRKS00024505 ).

Long-term outcomes in COVID-19 patients who recovered from the first wave of the pandemic.

This cross-sectional study evaluated the long-term health effects of coronavirus disease 2019 (COVID-19) in Jianghan District (Wuhan, China). The results showed that 61.4% of COVID-19 patients reported at least one symptom and 8.8% had depressive symptoms at the 17-month follow-up. The proportion of patients with chest radiographic abnormalities in Fangcang shelter hospitals and designated COVID-19 hospitals was 31.6% and 41.1%, respectively, and the proportion of patients with impaired pulmonary diffusion capacity in these hospitals was 52.8% and 60.9%, respectively. Female sex (odds ratio [OR] = 1.48, 95% confidence interval [CI]: 1.16-1.88), severe disease (OR = 1.46, 95% CI: 1.01-2.10) and a higher number of initial symptoms (OR = 1.31, 95% CI: 1.23-1.40) were associated with the development of sequelae symptoms at 17 months. This study involving community-dwelling COVID-19 adults may help determine the long-term effects of COVID-19 during the first pandemic wave. Nonetheless, larger follow-up studies are needed to characterize the post-COVID-19 condition.

Animated, video entertainment-education to improve vaccine confidence globally during the COVID-19 pandemic: an online randomized controlled experiment with 24,000 participants.

BACKGROUND: Science-driven storytelling and entertainment-education (E-E) media demonstrate potential for promoting improved attitudes and behavioral intent towards health-related practices. Months after the outbreak of coronavirus disease 2019 (COVID-19), emerging research highlights the essential role of interventions to improve public confidence in the COVID-19 vaccine. To improve vaccine confidence, we designed three short, animated videos employing three research-informed pedagogical strategies. These can be distributed globally through social media platforms, because of their wordless and culturally accessible design. However, the effectiveness of short, animated storytelling videos, deploying various pedagogic strategies, needs to be explored across different global regions. METHODS/DESIGN: The present study is a multi-site, parallel group, randomized controlled trial (RCT) comparing the effectiveness of (i) a storytelling-instructional-humor approach, (ii) a storytelling-analogy approach, (iii) a storytelling-emotion-focused approach, and (iv) no video. For our primary outcomes, we will measure vaccine hesitancy, and for secondary outcomes, we will measure behavioral intent to seek vaccination and hope. Using online platforms, we will recruit 12,000 participants (aged 18-59 years) from the USA and China, respectively, yielding a total sample size of 24,000. DISCUSSION: This trial uses innovative online technology, reliable randomization algorithms, validated survey instruments, and list experiments to establish the effectiveness of three short, animated videos employing various research-informed pedagogical strategies. Results will be used to scientifically support the broader distribution of these short, animated video as well as informing the design of future videos for rapid, global public health communication. TRIAL REGISTRATION: German Clinical Trials Register DRKS #00023650 . Date of registration: 2021/02/09.

Childhood vaccine uptake in Africa: threats, challenges, and opportunities

Childhood vaccination is a highly effective public health intervention for reducing childhood mortality and morbidity. This review discusses the factors that have been shown to influence vaccination uptake in Africa. African countries should develop effective strategies to address failures and challenges faced with vaccination uptake and hesitancy for it to achieve high vaccination coverage and reduction of vaccine preventable diseases. This is particularly important because of the likely short-term decline in foreign aid due to the economic recession arising from the prevailing coronavirus disease 2019 pandemic.

Attitudes Toward the Global Allocation of Chinese COVID-19 Vaccines: Cross-sectional Online Survey of Adults Living in China.

BACKGROUND: COVID-19 vaccines are in short supply worldwide. China was among the first countries to pledge supplies of the COVID-19 vaccine as a global public product, and to date, the country has provided more than 600 million vaccines to more than 200 countries and regions with low COVID-19 vaccination rates. Understanding the public's attitude in China toward the global distribution of COVID-19 vaccines could inform global and national decisions, policies, and debates. OBJECTIVE: The aim of this study was to determine the attitudes of adults living in China regarding the global allocation of COVID-19 vaccines developed in China and how these attitudes vary across provinces and by sociodemographic characteristics. METHODS: We conducted a cross-sectional online survey among adults registered with the survey company KuRunData. The survey asked participants 31 questions about their attitudes regarding the global allocation of COVID-19 vaccines developed in China. We disaggregated responses by province and sociodemographic characteristics. All analyses used survey sampling weights. RESULTS: A total of 10,000 participants completed the questionnaire. Participants generally favored providing COVID-19 vaccines to foreign countries before fulfilling domestic needs (75.6%, 95% CI 74.6%-76.5%). Women (3778/4921, 76.8%; odds ratio 1.18, 95% CI 1.07-1.32; P=.002) and those living in rural areas (3123/4065, 76.8%; odds ratio 1.13, 95% CI 1.01-1.27; P=.03) were especially likely to hold this opinion. Most respondents preferred providing financial support through international platforms rather than directly offering support to individual countries (72.1%, 95% CI 71%-73.1%), while for vaccine products they preferred direct provision to relevant countries instead of via a delivery platform such as COVAX (77.3%, 95% CI 76.3%-78.2%). CONCLUSIONS: Among our survey sample, we found that adults are generally supportive of the international distribution of COVID-19 vaccines, which may encourage policy makers to support and implement the distribution of COVID-19 vaccines developed in China worldwide. Conducting similar surveys in other countries could help align policy makers' actions on COVID-19 vaccine distribution with the preferences of their constituencies.

Hope as a predictor for COVID-19 vaccine uptake in the US: a cross-sectional survey of 11,955 adults.

Widespread vaccine uptake is critical for ending the COVID-19 pandemic. As public health officials focus on overcoming vaccine hesitancy, simultaneously boosting hope may be equally important in the US. We analyzed data from an online cross-sectional survey conducted in June 2021. Participants were 11,955 US adults (ages 18-83) of various ethnicities, living in urban and rural settings. Of these, 71.3% had some college education. Mean age was 32.3 years and 72.4% reported being vaccinated against COVID-19. Main measures were COVID-19 self-reported vaccination status (vaccine uptake), vaccine hesitancy (Adult Vaccine Hesitancy Scale), and hope (Adult Hope Scale). The US grand mean hope score fell within the low-hope range. COVID-19 vaccine uptake was positively associated with hope, even after adjusting for vaccine hesitancy, gender, age, ethnicity, income, and urban vs. rural residence. The strong relationship between hope, vaccine confidence and vaccine uptake persisted across US populations at risk for low vaccine uptake. Our mediation analysis revealed that, for every unit increase in hope, the probability of being vaccinated went up by 5% points. Of this association, 52% was not mediated by vaccine hesitancy, but rather through a direct pathway from hope to vaccine uptake. Mediation analyses of US populations at risk of low vaccine uptake revealed similar findings. Hope may play an important role in vaccine uptake by reducing vaccine hesitancy and by directly enhancing vaccine uptake. Especially in populations at risk of low vaccine uptake, vaccine interventions that boost hope may augment public health efforts to increase US vaccination rates.

Prevalence of depression in China during the early stage of the COVID-19 pandemic: a cross-sectional study in an online survey sample.

OBJECTIVES: We aimed to determine (1) the prevalence of depression during the COVID-19 pandemic among Chinese adults and (2) how depression prevalence varied by province and sociodemographic characteristics. DESIGN: Cross-sectional study. SETTING: National online survey in China. PARTICIPANTS: We conducted a cross-sectional online survey among adults registered with the survey company KuRunData from 8 May 2020 to 8 June 2020. We aimed to recruit 300-360 adults per province (n=14 493), with a similar distribution by sex and rural-urban residency as the general population within each of these provinces. PRIMARY OUTCOME: Participants completed the Patient Health Questionaire-9 (PHQ-9). We calculated the prevalence of depression (defined as a PHQ-9 score ≥10) nationally and separately for each province. ANALYSIS: Covariate-unadjusted and covariate-adjusted logistic regression models were used to examine how the prevalence of depression varied by adults' sociodemographic characteristics. All analyses used survey sampling weights. RESULTS: The survey was initiated by 14 493 participants, with 10 000 completing all survey questions and included in the analysis. The prevalence of depression in the national sample was 6.3% (95% CI 5.7% to 6.8%). A higher odds of depression was associated with living in an urban area (OR 1.50; 95% CI 1.18 to 1.90) and working as a nurse (OR 3.06; 95% CI 1.41 to 6.66). A lower odds of depression was associated with participants who had accurate knowledge of COVID-19 transmission prevention actions (OR 0.71; 95% CI 0.51 to 0.98), the knowledge that saliva is a main transmission route (OR 0.80; 95% CI 0.64 to 0.99) and awareness of COVID-19 symptoms (OR, 0.82; 95% CI 0.68 to 1.00). CONCLUSION: Around one in 20 adults in our online survey sample had a PHQ-9 score suggestive of depression. Interventions and policies to prevent and treat depression during the COVID-19 pandemic in China may be particularly needed for nurses and those living in urban areas.

OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany.

Mathematical models in epidemiology are an indispensable tool to determine the dynamics and important characteristics of infectious diseases. Apart from their scientific merit, these models are often used to inform political decisions and interventional measures during an ongoing outbreak. However, reliably inferring the epidemical dynamics by connecting complex models to real data is still hard and requires either laborious manual parameter fitting or expensive optimization methods which have to be repeated from scratch for every application of a given model. In this work, we address this problem with a novel combination of epidemiological modeling with specialized neural networks. Our approach entails two computational phases: In an initial training phase, a mathematical model describing the epidemic is used as a coach for a neural network, which acquires global knowledge about the full range of possible disease dynamics. In the subsequent inference phase, the trained neural network processes the observed data of an actual outbreak and infers the parameters of the model in order to realistically reproduce the observed dynamics and reliably predict future progression. With its flexible framework, our simulation-based approach is applicable to a variety of epidemiological models. Moreover, since our method is fully Bayesian, it is designed to incorporate all available prior knowledge about plausible parameter values and returns complete joint posterior distributions over these parameters. Application of our method to the early Covid-19 outbreak phase in Germany demonstrates that we are able to obtain reliable probabilistic estimates for important disease characteristics, such as generation time, fraction of undetected infections, likelihood of transmission before symptom onset, and reporting delays using a very moderate amount of real-world observations.

Factors Predicting Progression to Severe COVID-19: A Competing Risk Survival Analysis of 1753 Patients in Community Isolation in Wuhan, China.

Most studies of coronavirus disease 2019 (COVID-19) progression have focused on the transfer of patients within secondary or tertiary care hospitals from regular wards to intensive care units. Little is known about the risk factors predicting the progression to severe COVID-19 among patients in community isolation, who are either asymptomatic or suffer from only mild to moderate symptoms. Using a multivariable competing risk survival analysis, we identify several important predictors of progression to severe COVID-19-rather than to recovery-among patients in the largest community isolation center in Wuhan, China from 6 February 2020 (when the center opened) to 9 March 2020 (when it closed). All patients in community isolation in Wuhan were either asymptomatic or suffered from mild to moderate COVID-19 symptoms. We performed competing risk survival analysis on time-to-event data from a cohort study of all COVID-19 patients (n = 1753) in the isolation center. The potential predictors we investigated were the routine patient data collected upon admission to the isolation center: age, sex, respiratory symptoms, gastrointestinal symptoms, general symptoms, and computed tomography (CT) scan signs. The main outcomes were time to severe COVID-19 or recovery. The factors predicting progression to severe COVID-19 were: male sex (hazard ratio (HR) = 1.29, 95% confidence interval (CI) 1.04-1.58, p = 0.018), young and old age, dyspnea (HR = 1.58, 95% CI 1.24-2.01, p < 0.001), and CT signs of ground-glass opacity (HR = 1.39, 95% CI 1.04-1.86, p = 0.024) and infiltrating shadows (HR = 1.84, 95% CI 1.22-2.78, p = 0.004). The risk of progression was found to be lower among patients with nausea or vomiting (HR = 0.53, 95% CI 0.30-0.96, p = 0.036) and headaches (HR = 0.54, 95% CI 0.29-0.99, p = 0.046). Our results suggest that several factors that can be easily measured even in resource-poor settings (dyspnea, sex, and age) can be used to identify mild COVID-19 patients who are at increased risk of disease progression. Looking for CT signs of ground-glass opacity and infiltrating shadows may be an affordable option to support triage decisions in resource-rich settings. Common and unspecific symptoms (headaches, nausea, and vomiting) are likely to have led to the identification and subsequent community isolation of COVID-19 patients who were relatively unlikely to deteriorate. Future public health and clinical guidelines should build on this evidence to improve the screening, triage, and monitoring of COVID-19 patients who are asymtomatic or suffer from mild to moderate symptoms.

Macro-level efficiency of health expenditure: Estimates for 15 major economies.

The coronavirus disease 2019 (COVID-19) pandemic highlights the importance of strong and resilient health systems. Yet how much a society should spend on healthcare is difficult to determine because additional health expenditures imply lower expenditures on other types of consumption. Furthermore, the welfare-maximizing ("efficient") aggregate amount and composition of health expenditures depend on efficiency concepts at three levels that often get blurred in the debate. While the understanding of efficiency is good at the micro- and meso-levels-that is, relating to minimal spending for a given bundle of treatments and to the optimal mix of different treatments, respectively-this understanding rarely links to the efficiency of aggregate health expenditure at the macroeconomic level. While micro- and meso-efficiency are necessary for macro-efficiency, they are not sufficient. We propose a novel framework of a macro-efficiency score to assess welfare-maximizing aggregate health expenditure. This allows us to assess the extent to which selected major economies underspend or overspend on health relative to their gross domestic products per capita. We find that all economies under consideration underspend on healthcare with the exception of the United States. Underspending is particularly severe in China, India, and the Russian Federation. Our study emphasizes that the major and urgent issue in many countries is underspending on health at the macroeconomic level, rather than containing costs at the microeconomic level.

The economic burden of COVID-19 in the United States: Estimates and projections under an infection-based herd immunity approach.

OBJECTIVES: To assess the economic burden of COVID-19 that would arise absent behavioral or policy responses under the herd immunity approach in the United States and compare it to the total burden that also accounts for estimates of the value of lives lost. METHODS: We use the trajectories of age-specific human and physical capital in the production process to calculate output changes based on a human capital-augmented production function. We also calculate the total burden that results when including the value of lives lost as calculated from mortality rates of COVID-19 and estimates for the value of a statistical life in the United States based on studies assessing individual's willingness to pay to avoid risks. RESULTS: Our results indicate that the GDP loss associated with unmitigated COVID-19 would amount to a cumulative US$1.4 trillion by 2030 assuming that 60 percent of the population is infected over three years. This is equivalent to around 7.7 percent of GDP in 2019 (in constant 2010 US$) or an average tax on yearly output of 0.6 percent. After applying the value of a statistical life to account for the value of lives lost, our analyses show that the total burden can mount to between US$17 and 94 trillion over the next decade, which is equivalent to an annual tax burden between 8 and 43 percent. CONCLUSION: Our results show that the United States would incur a sizeable burden if it adopted a non-interventionist herd immunity approach. FUNDING: Research reported in this paper was supported by the Alexander von Humboldt Foundation, the Bill & Melinda Gates Foundation (Project INV-006261), and the Sino-German Center for Research Promotion (Project C-0048), which is funded by the German Research Foundation (DFG) and the National Natural Science Foundation of China (NSFC). Preparation of this article was also supported by the Value of Vaccination Research Network (VoVRN) through a grant from the Bill & Melinda Gates Foundation (Grant OPP1158136). The content is solely the responsibility of the authors.

Knowledge About COVID-19 Among Adults in China: Cross-sectional Online Survey.

BACKGROUND: A detailed understanding of the public's knowledge and perceptions of COVID-19 could inform governments' public health actions in response to the pandemic. OBJECTIVE: The aim of this study was to determine the knowledge and perceptions of COVID-19 among adults in China and its variation among provinces and by sociodemographic characteristics. METHODS: Between May 8 and June 8, 2020, we conducted a cross-sectional online survey among adults in China who were registered with the private survey company KuRunData. We set a target sample size of 10,000 adults, aiming to sample 300-360 adults from each province in China. Participants were asked 25 questions that tested their knowledge about COVID-19, including measures to prevent infection, common symptoms, and recommended care-seeking behavior. We disaggregated responses by age; sex; education; province; household income; rural-urban residency; and whether or not a participant had a family member, friend, or acquaintance who they know to have been infected with SARS-CoV-2. All analyses used survey sampling weights. RESULTS: There were 5079 men and 4921 women who completed the questionnaire and were included in the analysis. Out of 25 knowledge questions, participants answered a mean and median of 21.4 (95% CI 21.3-21.4) and 22 (IQR 20-23) questions correctly, respectively. A total of 83.4% (95% CI 82.7%-84.1%) of participants answered four-fifths or more of the questions correctly. For at least one of four ineffective prevention measures (using a hand dryer, regular nasal irrigation, gargling mouthwash, and taking antibiotics), 68.9% (95% CI 68.0%-69.8%) of participants answered that it was an effective method to prevent a SARS-CoV-2 infection. Although knowledge overall was similar across provinces, the percent of participants who answered the question on recommended care-seeking behavior correctly varied from 47.0% (95% CI 41.4%-52.7%) in Tibet to 87.5% (95% CI 84.1%-91.0%) in Beijing. Within provinces, participants who were male, were middle-aged, were residing in urban areas, and had higher household income tended to answer a higher proportion of the knowledge questions correctly. CONCLUSIONS: This online study of individuals across China suggests that the majority of the population has good knowledge of COVID-19. However, a substantial proportion still holds misconceptions or incorrect beliefs about prevention methods and recommended health care-seeking behaviors, especially in rural areas and some less wealthy provinces in Western China. This study can inform the development of tailored public health policies and promotion campaigns by identifying knowledge areas for which misconceptions are comparatively common and provinces that have relatively low knowledge.

Correction: Knowledge About COVID-19 Among Adults in China: Cross-sectional Online Survey.

[This corrects the article DOI: 10.2196/26940.].

Climate and the spread of COVID-19.

Visual inspection of world maps shows that coronavirus disease 2019 (COVID-19) is less prevalent in countries closer to the equator, where heat and humidity tend to be higher. Scientists disagree how to interpret this observation because the relationship between COVID-19 and climatic conditions may be confounded by many factors. We regress the logarithm of confirmed COVID-19 cases per million inhabitants in a country against the country's distance from the equator, controlling for key confounding factors: air travel, vehicle concentration, urbanization, COVID-19 testing intensity, cell phone usage, income, old-age dependency ratio, and health expenditure. A one-degree increase in absolute latitude is associated with a 4.3% increase in cases per million inhabitants as of January 9, 2021 (p value < 0.001). Our results imply that a country, which is located 1000 km closer to the equator, could expect 33% fewer cases per million inhabitants. Since the change in Earth's angle towards the sun between equinox and solstice is about 23.5°, one could expect a difference in cases per million inhabitants of 64% between two hypothetical countries whose climates differ to a similar extent as two adjacent seasons. According to our results, countries are expected to see a decline in new COVID-19 cases during summer and a resurgence during winter. However, our results do not imply that the disease will vanish during summer or will not affect countries close to the equator. Rather, the higher temperatures and more intense UV radiation in summer are likely to support public health measures to contain SARS-CoV-2.

Healthcare worker attendance during the early stages of the COVID-19 pandemic: A longitudinal analysis of fingerprint-verified data from all public-sector secondary and tertiary care facilities in Bangladesh.

BACKGROUND: The COVID-19 pandemic has overwhelmed hospitals in several areas in high-income countries. An effective response to this pandemic requires health care workers (HCWs) to be present at work, particularly in low- and middle-income countries (LMICs) where they are already in critically low supply. To inform whether and to what degree policymakers in Bangladesh, and LMICs more broadly, should expect a drop in HCW attendance as COVID-19 continues to spread, this study aims to determine how HCW attendance has changed during the early stages of the COVID-19 pandemic in Bangladesh. METHODS: This study analyzed daily fingerprint-verified attendance data from all 527 public-sector secondary and tertiary care facilities in Bangladesh to describe HCW attendance from January 26, 2019 to March 22, 2020, by cadre, hospital type, and geographic division. We then regressed HCW attendance onto fixed effects for day-of-week, month, and hospital, as well as indicators for each of three pandemic periods: a China-focused period (January 11, 2020 (first confirmed COVID-19 death in China) until January 29, 2020), international-spread period (January 30, 2020 (World Health Organization's declaration of a global emergency) until March 6, 2020), and local-spread period (March 7, 2020 (first confirmed COVID-19 case in Bangladesh) until the end of the study period). FINDINGS: On average between January 26, 2019 and March 22, 2020, 34.1% of doctors, 64.6% of nurses, and 70.6% of other health care staff were present for their scheduled shift. HCWs' attendance rate increased with time in 2019 among all cadres. Nurses' attendance level dropped by 2.5% points (95% confidence interval (CI) = -3.2% to -1.8%) and 3.5% points (95% CI = -4.5% to -2.5%) during the international-spread and the local-spread periods of the COVID-19 pandemic, relative to the China-focused period. Similarly, the attendance level of other health care staff declined by 0.3% points (95% CI = -0.8% to 0.2%) and 2.3% points (95% CI = -3.0% to -1.6%) during the international-spread and local-spread periods, respectively. Among doctors, however, the international-spread and local-spread periods were associated with a statistically significant increase in attendance by 3.7% points (95% CI = 2.5% to 4.8%) and 4.9% points (95% CI = 3.5% to 6.4%), respectively. The reduction in attendance levels across all HCWs during the local-spread period was much greater at large hospitals, where the majority of COVID-19 testing and treatment took place, than that at small hospitals. CONCLUSIONS: After a year of significant improvements, HCWs' attendance levels among nurses and other health care staff (who form the majority of Bangladesh's health care workforce) have declined during the early stages of the COVID-19 pandemic. This finding may portend an even greater decrease in attendance if COVID-19 continues to spread in Bangladesh. Policymakers in Bangladesh and similar LMICs should undertake major efforts to achieve high attendance levels among HCWs, particularly nurses, such as by providing sufficient personal protective equipment as well as monetary and non-monetary incentives.