Impact of essential workers in the context of social distancing for epidemic control

New emerging infectious diseases are identified every year, a subset of which become global pandemics like COVID-19. In the case of COVID-19, many governments have responded to the ongoing pandemic by imposing social policies that restrict contacts outside of the home, resulting in a large fraction of the workforce either working from home or not working. To ensure essential services, however, a substantial number of workers are not subject to these limitations, and maintain many of their pre-intervention contacts. To explore how contacts among such “essential” workers, and between essential workers and the rest of the population, impact disease risk and the effectiveness of pandemic control, we evaluated several mathematical models of essential worker contacts within a standard epidemiology framework. The models were designed to correspond to key characteristics of cashiers, factory employees, and healthcare workers. We find in all three models that essential workers are at substantially elevated risk of infection compared to the rest of the population, as has been documented, and that increasing the numbers of essential workers necessitates the imposition of more stringent controls on contacts among the rest of the population to manage the pandemic. Importantly, however, different archetypes of essential workers differ in both their individual probability of infection and impact on the broader pandemic dynamics, highlighting the need to understand and target intervention for the specific risks faced by different groups of essential workers. These findings, especially in light of the massive human costs of the current COVID-19 pandemic, indicate that contingency plans for future epidemics should account for the impacts of essential workers on disease spread.

Applying User-Centered Design Methods to Understand Users' Day-to-Day Experiences Can Inform a Mobile Intervention for Binge Eating and Weight Management

Introduction: Weight loss apps to date have not directly addressed binge eating. To inform the design of a new mobile behavioral intervention that addresses binge eating and weight management, we applied user-centered design methods to qualitatively assess how target intervention consumers experience these conditions in their day-to-day lives.Methods: The participants were 22 adults with self-reported obesity (body mass index ≥30) and recurrent binge eating (≥12 episodes in 3 months) who were interested in losing weight and reducing binge eating. The participants completed a digital diary study, which is a user-centered design technique for capturing individuals' day-to-day experiences in relevant contexts. Qualitative data describing the participants' experiences with binge eating and obesity were analyzed using thematic analysis. The results were then used to create personas (i.e., character archetypes of different intervention consumers).Results: The participants described triggers for binge eating and indicated that binge eating and excess weight negatively impact their mental health, physical health, and quality of life. The resulting personas reflected five different struggles individuals with these health problems experience in managing their binge eating and weight.Conclusions: Individuals with binge eating and obesity have varying precipitants of problematic eating as well as varying motivations for and challenges to behavior change. To meet the needs of all who seek intervention, an ideal intervention design will account for variations in these factors and be relevant to diverse experiences. Insights from the diary study and resulting personas will inform the next phases of the user-centered design process of iteratively designing prototypes and testing the intervention in practice.

COVID-19 Vaccination Willingness among Chinese Adults under the Free Vaccination Policy

(1) Background: China will provide free coronavirus disease 2019 (COVID-19) vaccinations for the entire population. This study analyzed the COVID-19 vaccination willingness rate (VWR) and its determinants under China’s free vaccination policy compared to a paid vaccine. (2) Methods: Data on 2377 respondents were collected through a nationwide questionnaire survey. Multivariate ordered logistic regression models were specified to explore the correlation between the VWR and its determinants. (3) Results: China’s free vaccination policy for COVID-19 increased the VWR from 73.62% to 82.25% of the respondents. Concerns about the safety and side-effects were the primary reason for participants’ unwillingness to be vaccinated against COVID-19. Age, medical insurance and vaccine safety were significant determinants of the COVID-19 VWR for both the paid and free vaccine. Income, occupation and vaccine effectiveness were significant determinants of the COVID-19 VWR for the free vaccine. (4) Conclusions: Free vaccinations increased the COVID-19 VWR significantly. People over the age of 58 and without medical insurance should be treated as the target intervention population for improving the COVID-19 VWR. Contrary to previous research, high-income groups and professional workers should be intervention targets to improve the COVID-19 VWR. Strengthening nationwide publicity and education on COVID-19 vaccine safety and effectiveness are recommended policies for decision-makers.

Intersectionality and Smoking Cessation: Exploring Various Approaches for Understanding Health Inequities

Objective Many marginalized groups smoke at higher rates and have greater difficulty quitting than less marginalized groups. Most research on smoking cessation inequities has focused on a single sociodemographic attribute (eg, race or socioeconomic status), yet individuals possess multiple attributes that may increase risk. The current study used an intersectionality framework to examine how the interplay between multiple marginalized attributes may impact smoking cessation outcomes. Methods A diverse sample of 344 adults enrolled in a smoking cessation program and reported on sociodemographic attributes (eg, race/ethnicity, gender, income) and continuous smoking abstinence on their quit date and at 1, 2, and 4 weeks postquit date. A Cox proportional hazard regression model was used to estimate whether intersectional links among race/ethnicity, gender, and income were related to smoking cessation outcomes. Results Lower household income may be related to higher risk of smoking cessation failure. There were no significant interactions among race/ethnicity, gender, and income in predicting relapse. Pairwise intersectional group differences suggested some groups may be at higher risk of relapse. Number of marginalized sociodemographic attributes did not predict relapse. Conclusions Intersectionality may be a promising framework for addressing health inequities, and may help elucidate how to best design and target intervention efforts for individuals characterized by sociodemographic intersections that concur particularly high risk for poor tobacco cessation outcomes. Implications Despite an overall decline in smoking rates, socioeconomic inequities in smoking prevalence and cancer mortality are widening. Efforts targeting tobacco cessation should incorporate new theory to capture the complex set of factors that may account for tobacco cessation inequities (eg, multiple aspects of identity that may influence access to tobacco cessation treatment and exposure to certain stressors that impede cessation efforts). Intersectionality may be a promising framework for addressing health inequities in tobacco use and cessation and may help elucidate how to best design and target intervention efforts for individuals that concur particularly high risk for poor tobacco cessation outcomes.

Mosquito species and age influence thermal performance of traits relevant to malaria transmission

Models predicting disease transmission are a vital tool in the control of mosquito populations and malaria reduction as they can target intervention efforts. We compared the performance of temperature-dependent transmission models when mosquito life history traits were allowed to change across the lifespan of Anopheles stephensi, the urban malaria mosquito, to models parameterized with commonly derived estimates of lifetime trait values. We conducted an experiment on adult female An. stephensi to generate daily per capita values for lifespan, egg production, and biting rate at six constant temperatures. Both temperature and age significantly affected trait values. Further, we found quantitative and qualitative differences between temperature-trait relationships estimated based on daily rates versus directly observed lifetime values. Incorporating these temperature-trait relationships into an expression governing transmission suitability, relative R0(T), model resulted in minor differences in the breadth of suitable temperatures for Plasmodium falciparum transmission between the two models constructed from only An. stephensi trait data, but a substantial increase in breadth compared to a previously published model consisting of trait data from multiple mosquito species. Overall this work highlights the importance of considering how mosquito trait values vary with mosquito age and mosquito species when generating temperature-based environmental suitability predictions of transmission.

Crime, Intimidation, and Whistleblowing: A Theory of Inference from Unverifiable Reports

We consider a game between a principal, an agent, and a monitor in which the principal would like to rely on messages by the monitor (the potential whistleblower) to target intervention against a misbehaving agent. The difficulty is that the agent can credibly threaten to retaliate against the monitor in the event of an intervention. In this setting, intervention policies that are responsive to the monitor’s message provide informative signals to the agent, which can be used to target threats efficiently. Principals that are too responsive to information shut down communication channels. Successful intervention policies must therefore garble the information provided by monitors and cannot be fully responsive. We show that policy evaluation on the basis of non-verifiable whistleblower messages is feasible under arbitrary incomplete information provided policy design takes into account that messages are endogenous.

Trend Detection of Drug Abuse Using Multivariate Analysis in Malaysia During the Years 2005 to 2015

This study aims to dismantling number drug abuser, cohort of age and drug type effects to improve our understanding of these trends and suggested groups for target intervention by stakeholders to effectively reduce resultant harms. Data of the study involving number of drug abuser, cohort of age (8 groups: < 13, 13-15, 16-19, 20-24, 25-29, 30-34, 35-39, > 40) and drug type was obtained by reviewing annual report of National Anti-Drug Agency (NADA) of Malaysia during 2009 to 2015. Descriptive statistics were applied to give distribution rate and patterns of the data. Cluster analysis then performed to grouped age cohort and drug type into homogenous clusters. Mann – Kendall test were then applied at 5% interval level to identify any significant trends existed in all clusters. The result showed that age can be group into 3 clusters namely low-age cases, moderated-age cases and high-age cases, while for drug type 3 clusters were also created, low-drug type, moderate-drug type and high-drug type. Lastly, trend test shows that high-drug type (opiate) have very significant upward trend p < 0.05. Therefore, preventive strategies can be focus on young adult and opiate abused as it can greatly help reduce number of drug abuser in Malaysia.