Effect of COVID-19 response policies on walking behavior in US cities.
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ABSTRACT:
SUBMITTER: Hunter RF
PROVIDER: S-EPMC8209100 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:COVID-19 related policies in the USA can be confusing: some states, but not others, implemented mask mandates mid-pandemic, and states reopened their economies to different levels with different timelines after initial shutdowns. The current research asks: How well does the public's perception of such policies align with actual policies, and how well do actual versus perceived policies predict the public's mask-wearing and social distancing behaviors during the COVID-19 pandemic? We conducted a preregistered cross-sectional study among 1,073 online participants who were representative of the U.S. population on age, gender, and education on Monday-Tuesday, July 20-21, 2020. We asked participants which locations they visited in the past weekend, and their mask-wearing and social distancing behaviors at each location. We also measured participants' beliefs about their state's policies on mask mandate and business opening and obtained objective measures of these policies from publicly available data. Perception about the existence of mask mandate was 91% accurate in states with a mask mandate but only 46% accurate in states without one. Perception of state reopening level did not correlate with policy. It was the perceived but not actual state mask mandate that positively predicted both mask-wearing and social distancing, controlling for state COVID-19 cases, demographic factors, and participants' numeracy and COVID-19 history. The public's perception of state-level mask mandates erred on the side of assuming there is one. Perception of reopening is almost completely inaccurate. Paradoxically, public perception that a mask mandate exists predicts preventive behaviors better than actual mandates.
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Project description:A growing body of literature suggests that restrictive public health measures implemented to control COVID-19 have had negative impacts on physical activity. We examined how Stay Home orders in Houston, New York City, and Seattle impacted outdoor physical activity patterns, measured by daily bicycle and pedestrian count data. We assessed changes in activity levels between the period before and during Stay Home orders. Across all three cities, we found significant changes in bicycle and pedestrian counts from the period before to the period during Stay Home orders. The direction of change varied by location, likely due to differing local contexts and outbreak progression. These results can inform policy around the use of outdoor public infrastructure as the COVID-19 pandemic continues.
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Project description:IntroductionSeveral treatment options are available for COVID-19 to date. However, the use of a combination of non-pharmaceutical interventions (NPIs) is necessary for jurisdictions to contain its spread. Although the implementation cost of NPIs may be low from the healthcare system perspective, it can be costly when considering the indirect costs from the societal perspective. COVID-19 vaccination campaigns have begun in several countries worldwide. Nonetheless, the quantity of vaccines available remain limited over the next 1 to 2 years. A tool for informing vaccine prioritisation that considers both cost and effectiveness will be highly useful. This study aims to identify the most cost-effective combination of COVID-19 response policies, using Singapore as an example.Methods and analysisAn age-stratified Susceptible-Exposed-Infectious-Recovered model will be used to generate the number of infections stratified by disease severity under different intervention scenarios. Polices of interest include test-trace-isolate, travel restriction, compulsory face mask and hygiene practices, social distancing, dexamethasone/remdesivir therapy and vaccination. The latest phase 3 trial results and the WHO Target Product Profiles for COVID-19 vaccines will be used to model vaccine characteristics. A cost (expected resource utilisation and productivity losses) and quality-adjusted life years (QALYs) will be attached to these outputs for a cost-utility analysis. The primary outcome measure will be the incremental cost-effectiveness ratio generated from the incremental cost of policy alternatives expressed as a ratio of the incremental benefits (QALYs gained). Efficacy of policy options will be gathered from literature review and from its observed impacts in Singapore. Cost data will be gathered from healthcare institutions, Ministry of Health and published data. Sensitivity analysis such as threshold analysis and scenario analysis will be conducted.Ethics and disseminationEthics approval was not required for this study. The study findings will be disseminated through peer-reviewed journals.
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Project description:COVID-19 has had far-reaching global effects on the health and wellbeing of individuals on every continent. The economic and financial market response has been equally disastrous with high levels of volatility observed. This study explores the temporal relations between structural breaks, market volatility and government stay-at-home policy interventions and social distancing measures for 28 countries and their respective indices. We present results which indicate the establishment of stay-at-home policies influence sharp discontinuities in 15 of 28 markets (53.57 %) and increase market efficiency in 30 of 49 cases observed (61.22 %). These results indicate a small, statistically significant degree of stabilization in international financial markets responding to government stay-at-home policies and social distancing measures, a promising result for political actors concerned with economic performance during the public health response to the coronavirus 2019 pandemic.
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Project description:Do cities accelerate COVID-19 transmission? Increased transmission arising from population density prompts spatial policies for financial support and containment, and poorer prospects for recovery. Using daily case counts from over 3,000 counties in the U.S. from February to September 2020, I estimate a compartmental transmission equation. Rational sheltering behavior plausibly varies by location, so I propose two instruments that exploit unanticipated variation in exposure to potential infection. In the first month of local infections, an additional log point of population density raises the expected transmission parameter estimate by around 3%. After the first month, the relation vanishes: density effects occur only in the outbreaks. Public transport, work-from-home jobs and income explain additional variation in transmission but do not account for the density effects. Consistent with location-varying optimal sheltering behavior, I document stronger mobility declines in denser areas, but only after the first month of infections. These results suggest that differences in transmission between cities and other places do not motivate spatial policies for recovery or containment, or poorer prospects after the pandemic.
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Project description:This paper assesses the quantitative impact of government interventions on deaths related to the first COVID-19 outbreak. Using daily data for 32 countries and relying on the stringency of the conducted policies, we find that the greater the strength of government interventions at an early stage, the more effective these are in slowing down or reversing the growth rate of deaths. School closures have a significant impact on reducing the growth rate of deaths, which is less powerful compared to the case where a number of policy interventions are combined together. These results can be informative for governments in responding to future pandemics.
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Project description:Successful epidemic modeling requires understanding the implicit feedback control strategies used by populations to modulate the spread of contagion. While such strategies can be replicated with intricate modeling assumptions, here we propose a simple model where infection dynamics are described by a three parameter feedback policy. Rather than model individuals as directly controlling the contact rate which governs the spread of disease, we model them as controlling the contact rate's derivative, resulting in a dynamic rather than kinematic model. The feedback policy used by populations across the United States which best fits observations is proportional-derivative control, where learned parameters strongly correlate with observed interventions (e.g., vaccination rates and mobility restrictions). However, this results in a non-zero "steady-state" of case counts, implying current mitigation strategies cannot eradicate COVID-19. Hence, we suggest making implicit policies a function of cumulative cases, resulting in proportional-integral-derivative control with higher potential to eliminate COVID-19.
| S-EPMC9947911 | biostudies-literature
Project description:The present study investigates the effects of policies restricting human activities during the COVID-19 epidemic on the characteristics of Night Land Surface Temperature (NLST) and Night Urban Heat Islands (NUHI) in five major European cities. In fact, the focus of this study was to explore the role of anthropogenic factors in the formation and intensity of NUHI. The effect of such factors was uncontrollable before the COVID-19 outbreak on the global scale and in a real non-laboratory environment. In this study, two indices, the concentration of Nitrogen dioxide (NO2) and Nighttime Lights (NL), were used as indicators of the number of anthropogenic activities. The data were collected before the COVID-19 outbreak and after its prevalence in 2019-2020. A Paired samples t-test and a Pearson correlation were used to examine the differences or significant relationships between the variables and indicators studied throughout the two periods. The results of the study confirmed a direct and significant relationship between NO2 and NL indices and the NUHI and NLST variables; however, using strict restrictions during the COVID-19 pandemic, the NO2 and NL indices decreased seriously, leading to significant changes in the characteristics of the NUHI and NLST in the five cities. This study has some implications for urban planners and politicians, e.g., the environmental impacts of changing the nature and level of anthropogenic activities can greatly affect the pattern and intensity of the Urban Heat Islands (UHIs) (as a serious environmental challenge).
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Project description:Objective: This study aimed to investigate how COVID-19 prevention policies influenced the COVID-19 incidence in men and women. Methods: We conducted a retrospective longitudinal study using the Swiss Federal Office of Public Health and the Spanish Ministry of Health surveillance data for February 2020-June 2021 to explore sex and age differences in COVID-19 cases and testing. The female-male incidence rate ratios (IRR) were estimated for each week of the pandemic. We complemented our analysis with qualitative information on relevant containment measures in each country. Results: In Switzerland and in Spain, there was an excess of cases in women of 20-59 years old and 80+. This excess of cases was significant during the waves of the pandemic in both countries. In Switzerland, the biggest difference was observed for the age group 20-29, reaching an excess of 94% of cases compared to men during the first wave of COVID-19 (March-May 2020). The excess of cases in women was greater in Spain than in Switzerland, where it reached 159% for women aged 20-29 during the first wave (March-June 2020). In both countries, the age groups 60-79 had a significant excess of cases in men during the pandemic. Conclusion: COVID-19 public health policies affect men and women in different ways. Our findings highlight the importance of gender-sensitive responses to address a public health crisis.
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