Environmental risk factors of airborne viral transmission: Humidity, Influenza and SARS-CoV-2 in the Netherlands.

OBJECTIVE: The relationship between specific humidity and influenza/SARS-CoV-2 in the Netherlands is evaluated over time and at regional level. DESIGN: Parametric and non-parametric correlation coefficients are calculated to quantify the relationship between humidity and influenza, using five years of weekly data. Bayesian spatio-temporal models-with a Poisson and a Gaussian likelihood-are estimated to find the relationship between regional humidity and the daily cases of SARS-CoV-2 in the municipalities and provinces of the Netherlands. RESULTS: An inverse (negative) relationship is observed between specific humidity and the incidence of influenza between 2015 and 2019. The space-time analysis indicates that an increase of specific humidity of one gram of water vapor per kilogram of air (1 g/kg) is related to a reduction of approximately 5% in the risk of COVID-19 infections. CONCLUSIONS: The increase in humidity during the outbreak of the SARS-CoV-2 in the Netherlands may have helped to reduce the risk of regional COVID-19 infections. Policies that lead to an increase in household specific humidity to over 6g/Kg will help reduce the spread of respiratory viruses such as influenza and SARS-CoV-2.

Community Participation and Multidimensional Child Growth: Evidence from the Vietnam Young Lives Study.

Background: Community participation has the potential to improve the effects of interventions and reduce inequalities in child growth. Multidimensional indicators capture such effects and inequalities. Objectives: The objective of this study was to measure the association between multidimensional child growth and community participation in 2 nutrition-sensitive interventions. Methods: A Multidimensional Index of Child Growth was calculated with the 5-y-old cohort of the Vietnam Young Lives Survey. Young Lives is a unique dataset that has information on community participation in the design and implementation stages of 2 interventions: a health and a water, sanitation, and hygiene (WASH) intervention. Community participation during the interventions was recorded retrospectively with interviews at the household level. Ordinary least-squares and quantile regressions were estimated using data on 240 children. A Multidimensional Index of Child Advantage, sex, and location (urban/rural) were included as control covariates. Results: A positive association (post hoc statistical power = 0.859) was estimated for community participation during the design stage of the WASH intervention, particularly for the most deprived children (P < 0.05). Negative effects were estimated for the health intervention during the design stage (P < 0.05) and no significant effects were found for community participation during the implementation stage of the interventions. Instead of the physical dimension, the significant associations in the design stage were related to the nonphysical dimension of child growth. Inequalities in multidimensional growth were found for children living in rural areas, but not for girls. Conclusions: The association between community participation and multidimensional child growth is indicative of the importance of community participation during the design phase of interventions, in particular for the nonphysical dimensions of child growth related to social and psychological factors. The benefits of participation were greater for urban children compared with rural children, which deserves further attention.

Work-related and personal predictors of COVID-19 transmission: evidence from the UK and USA.

OBJECTIVE: To develop evidence of work-related and personal predictors of COVID-19 transmission. SETTING AND RESPONDENTS: Data are drawn from a population survey of individuals in the USA and UK conducted in June 2020. BACKGROUND METHODS: Regression models are estimated for 1467 individuals in which reported evidence of infection depends on work-related factors as well as a variety of personal controls. RESULTS: The following themes emerge from the analysis. First, a range of work-related factors are significant sources of variation in COVID-19 infection as indicated by self-reports of medical diagnosis or symptoms. This includes evidence about workplace types, consultation about safety and union membership. The partial effect of transport-related employment in regression models makes the chance of infection over three times more likely while in univariate analyses, transport-related work increases the risk of infection by over 40 times in the USA. Second, there is evidence that some home-related factors are significant predictors of infection, most notably the sharing of accommodation or a kitchen. Third, there is some evidence that behavioural factors and personal traits (including risk preference, extraversion and height) are also important. CONCLUSIONS: The paper concludes that predictors of transmission relate to work, transport, home and personal factors. Transport-related work settings are by far the greatest source of risk and so should be a focus of prevention policies. In addition, surveys of the sort developed in this paper are an important source of information on transmission pathways within the community.