Mask-wearing and control of SARS-CoV-2 transmission in the USA: a cross-sectional study.

BACKGROUND: Face masks have become commonplace across the USA because of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic. Although evidence suggests that masks help to curb the spread of the disease, there is little empirical research at the population level. We investigate the association between self-reported mask-wearing, physical distancing, and SARS-CoV-2 transmission in the USA, along with the effect of statewide mandates on mask uptake. METHODS: Serial cross-sectional surveys were administered via a web platform to randomly surveyed US individuals aged 13 years and older, to query self-reports of face mask-wearing. Survey responses were combined with instantaneous reproductive number (Rt) estimates from two publicly available sources, the outcome of interest. Measures of physical distancing, community demographics, and other potential sources of confounding (from publicly available sources) were also assessed. We fitted multivariate logistic regression models to estimate the association between mask-wearing and community transmission control (Rt<1). Additionally, mask-wearing in 12 states was evaluated 2 weeks before and after statewide mandates. FINDINGS: 378 207 individuals responded to the survey between June 3 and July 27, 2020, of which 4186 were excluded for missing data. We observed an increasing trend in reported mask usage across the USA, although uptake varied by geography. A logistic model controlling for physical distancing, population demographics, and other variables found that a 10% increase in self-reported mask-wearing was associated with an increased odds of transmission control (odds ratio 3·53, 95% CI 2·03-6·43). We found that communities with high reported mask-wearing and physical distancing had the highest predicted probability of transmission control. Segmented regression analysis of reported mask-wearing showed no statistically significant change in the slope after mandates were introduced; however, the upward trend in reported mask-wearing was preserved. INTERPRETATION: The widespread reported use of face masks combined with physical distancing increases the odds of SARS-CoV-2 transmission control. Self-reported mask-wearing increased separately from government mask mandates, suggesting that supplemental public health interventions are needed to maximise adoption and help to curb the ongoing epidemic. FUNDING: Flu Lab, Google.org (via the Tides Foundation), National Institutes for Health, National Science Foundation, Morris-Singer Foundation, MOOD, Branco Weiss Fellowship, Ending Pandemics, Centers for Disease Control and Prevention (USA).

Mask Wearing and Control of SARS-CoV-2 Transmission in the United States.

INTRODUCTION: Cloth face coverings and surgical masks have become commonplace across the United States in response to the SARS-CoV-2 epidemic. While evidence suggests masks help curb the spread of respiratory pathogens, population level, empirical research remains limited. Face masks have quickly become a topic of public debate as government mandates have started requiring their use. Here we investigate the association between self-reported mask wearing, social distancing and community SARS-CoV-2 transmission in the United States, as well as the effect of statewide mandates on mask uptake. METHODS: Serial cross-sectional surveys were administered June 3 through July 27, 2020 via a web platform. Surveys queried individuals' likelihood to wear a face mask to the grocery store or with family and friends. Responses (N = 378,207) were aggregated by week and state and combined with measures of the instantaneous reproductive number (R t ), social distancing proxies, respondent demographics and other potential sources of confounding. We fit multivariate logistic regression models to estimate the association between mask wearing and community transmission control (R t <1) for each state and week. Multiple sensitivity analyses were considered to corroborate findings across mask wearing definitions, R t estimators and data sources. Additionally, mask wearing in 12 states was evaluated two weeks before and after statewide mandates. RESULTS: We find an increasing trend in mask usage across the U.S., although uptake varies by geography and demographic groups. A multivariate logistic model controlling for social distancing and other variables found a 10% increase in mask wearing was associated with a 3.53 (95% CI: 2.03, 6.43) odds of transmission control (R t <1). We also find that communities with high mask wearing and social distancing have the highest predicted probability of a controlled epidemic. These positive associations were maintained across sensitivity analyses. Following state mandates, mask wearing did not show significant statistical changes in uptake, however the positive trend of increased mask wearing over time was preserved. CONCLUSION: Widespread utilization of face masks combined with social distancing increases the odds of SARS-CoV-2 transmission control. Mask wearing rose separately from government mask mandates, suggesting supplemental public health interventions are needed to maximize mask adoption and disrupt the spread of SARS-CoV-2, especially as social distancing measures are relaxed.

Surveillance in eradication and elimination of infectious diseases: a progression through the years.

During the years since certification of smallpox eradication, the power of infectious disease surveillance has been greatly increased by new biotechnical and electronic technologies. These technologies have transformed the way that surveillance can be used to contribute to public health, and to infectious disease eradication and elimination. In addition to permitting precise geographical placement of infections by incorporating the most up to date geographical positioning systems, infectious disease surveillance can now also provide more comprehensive understanding of the spread and risks of infections because of genomic sequencing that leads to more meaningful epidemiological analysis. These new technologies have made infectious disease surveillance an even more powerful and timely tool than it was during the period of smallpox eradication. Future surveillance will continue to refine these technologies, and adapt newer ones such as rapid point of care diagnostics and hand held communication devices that will lead to more timely and accurate reporting from health facilities. These technologies will also lead to the possibility of direct participation in surveillance by individuals who will be able to report their own disease syndromes, those of their neighbors, or those of domestic and wild animals at the animal/human interface.

Detecting influenza epidemics using search engine query data.

Seasonal influenza epidemics are a major public health concern, causing tens of millions of respiratory illnesses and 250,000 to 500,000 deaths worldwide each year. In addition to seasonal influenza, a new strain of influenza virus against which no previous immunity exists and that demonstrates human-to-human transmission could result in a pandemic with millions of fatalities. Early detection of disease activity, when followed by a rapid response, can reduce the impact of both seasonal and pandemic influenza. One way to improve early detection is to monitor health-seeking behaviour in the form of queries to online search engines, which are submitted by millions of users around the world each day. Here we present a method of analysing large numbers of Google search queries to track influenza-like illness in a population. Because the relative frequency of certain queries is highly correlated with the percentage of physician visits in which a patient presents with influenza-like symptoms, we can accurately estimate the current level of weekly influenza activity in each region of the United States, with a reporting lag of about one day. This approach may make it possible to use search queries to detect influenza epidemics in areas with a large population of web search users.