Low Barrier Tele-Buprenorphine in the Time of COVID-19: A Case Report

Background: To reduce the spread of coronavirus disease 2019 (COVID-19), many substance use disorder treatment programs have transitioned to telemedicine. Emergency regulatory changes allow buprenorphine initiation without an in-person visit. We describe the use of videoconferencing for buprenorphine initiation combined with street outreach to engage 2 patients experiencing homelessness with severe opioid use disorder (OUD). Case Presentation: Patient 1 was a 30-year-old man with severe OUD who had relapsed to injection heroin/fentanyl after incarceration. A community drop-in center outreach harm reduction specialist facilitated a videoconference with an addiction specialist at an OUD bridge clinic. The patient completed a community buprenorphine/naloxone initiation and self-titrated to his prior dose, 8/2 mg twice daily. One week later, he reconnected with the outreach team for a follow-up videoconference visit. Patient 2, a 36-year-old man with severe OUD, connected to the addiction specialist via a syringe service program harm reduction specialist. He had been trying to connect to a community buprenorphine/naloxone provider, but access was limited due to COVID-19, so he was using diverted buprenorphine/naloxone to reduce opioid use. He was restarted on his previous dose of 12/3 mg daily which was continued via phone follow-up 16 days later. Conclusion(s): COVID-19-related regulatory changes allow buprenorphine initiation via telemedicine. We describe 2 cases where telemedicine was combined with street outreach to connect patients experiencing homelessness with OUD to treatment. These cases highlight an important opportunity to provide access to life-saving OUD treatment for vulnerable patients in the setting of a pandemic that mandates reduced face-to-face clinical interactions.Copyright © 2020 Lippincott Williams and Wilkins. All rights reserved.

Towards an ethical and trustworthy of virtual work environment in current workplace

It is constructed via community interchange philosophy, a research observes an impact related to relational or informational work environment over ethical business as well job involvement through corporate crises affected via pandemic of COVID-19. A works examination was conducted via freshly printed articles for locating studies concerning ethics of work environment and COVID-19 in current worldwide market. Including strategy of best practice with current circumstances, explain current learning basis, gap during practice & zones which might need improvement and further study. Outcomes indicate that to control such increase related to pandemic of COVID-19 did increase remoting working workplace with virtual work situation. Such outcomes can produce a necessity of experiential investigation for an impact related to virtual work environment as well as active behaviors for supporting such requirements or consequences related to persons that might be around red zone that or feeling misuse or abandonment although defensive, socially isolating and once occupied within a situation in social-distancing is mandatory. Research is established by analysis or assessment related to issued researches ae well as current workplace circumstances none of different forms of study. Small is common regarding ethical woke environment practice in era related to COVID-19, remote working, social-distancing or remote-working. research enhances body related to awareness within field. © 2023 University of Bahrain. All rights reserved.

When ostracism is mandated: COVID-19, social distancing, and psychological needs.

Social distancing to limit the spread of COVID-19 poses a unique psychological challenge, especially in light of evidence for the importance of even minimal cues of inclusion. In a German (N = 546) and a US (N = 199) sample, we examined the impact of work-related social distancing on the outcomes of ostracism, measuring need fulfillment in self-esteem, belonging, control, and meaning. Overall, social distancing was associated with decreased need fulfillment. German participants reported a higher need fulfillment compared to American participants. Compared to previous studies, social distancing impacted self-related need fulfillment less than experimental manipulations of ostracism, however more so than the baseline condition of inclusion. Working, while social distancing was associated with greater need fulfillment, as was identifying as male. Women reported lower need fulfillment overall and this difference was mediated by the need to belong. Results are discussed in terms of understanding self-related needs in different contexts of isolation.

A hybrid deep learning based approach for the prediction of social distancing among individuals in public places during Covid19 pandemic

Social distance is considered one of the most effective prevention techniques to prevent the spread of Covid19 disease. To date, there is no proper system available to monitor whether social distancing protocol is being followed by individuals or not in public places. This research has proposed a hybrid deep learning-based model for predicting whether individuals maintain social distancing in public places through video object detection. This research has implemented a customized deep learning model using Detectron2 and IOU for monitoring the process. The base model adapted is RCNN and the optimization algorithm used is Stochastic Gradient Descent algorithm. The model has been tested on real time images of people gathered in textile shops to demonstrate the real time application of the developed model. The performance evaluation of the proposed model reveals that the precision is 97.9% and the mAP value is 84.46, which makes it clear that the model developed is good in monitoring the adherence of social distancing by individuals. [ FROM AUTHOR]

A hybrid deep learning based approach for the prediction of social distancing among individuals in public places during Covid19 pandemic

Social distance is considered one of the most effective prevention techniques to prevent the spread of Covid19 disease. To date, there is no proper system available to monitor whether social distancing protocol is being followed by individuals or not in public places. This research has proposed a hybrid deep learning-based model for predicting whether individuals maintain social distancing in public places through video object detection. This research has implemented a customized deep learning model using Detectron2 and IOU for monitoring the process. The base model adapted is RCNN and the optimization algorithm used is Stochastic Gradient Descent algorithm. The model has been tested on real time images of people gathered in textile shops to demonstrate the real time application of the developed model. The performance evaluation of the proposed model reveals that the precision is 97.9% and the mAP value is 84.46, which makes it clear that the model developed is good in monitoring the adherence of social distancing by individuals. [ FROM AUTHOR] Copyright of Journal of Intelligent & Fuzzy Systems is the property of IOS Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Path to normality: Assessing the level of social-distancing measures relaxation against antibody-resistant SARS-CoV-2 variants in a partially-vaccinated population.

Introduction: Two years into the coronavirus 2019 (COVID-19) pandemic, populations with less built-up immunity continued to devise ways to optimize social distancing measures (SDMs) relaxation levels for outbreaks triggered by SARS-CoV-2 and its variants to resume minimal economics activities while avoiding hospital system collapse. Method: An age-stratified compartmental model featuring social mixing patterns was first fitted the incidence data in second wave in Hong Kong. Hypothetical scenario analysis was conducted by varying population mobility and vaccination coverages (VCs) to predict the number of hospital and intensive-care unit admissions in outbreaks initiated by ancestral strain and its variants (Alpha, Beta, Gamma, Delta and Omicron). Scenarios were "unsustainable" if either of admissions was larger than the maximum of its occupancy. Results: At VC of 65%, scenarios of full SDMs relaxation (mean daily social encounters prior to COVID-19 pandemic = 14.1 contacts) for outbreaks triggered by ancestral strain, Alpha and Beta were sustainable. Restricting levels of SDMs was required such that the optimal population mobility had to be reduced to 0.9, 0.65 and 0.37 for Gamma, Delta and Omicron associated outbreaks respectively. VC improvement from 65% to 75% and 95% allowed complete SDMs relaxation in Gamma-, and Delta-driven epidemic respectively. However, this was not supported for Omicron-triggered epidemic. Discussion: To seek a path to normality, speedy vaccine and booster distribution to the majority across all age groups is the first step. Gradual or complete SDMs lift could be considered if the hybrid immunity could be achieved due to high vaccination coverage and natural infection rate among vaccinated or the COVID-19 case fatality rate could be reduced similar to that for seasonal influenza to secure hospital system sustainability.

Keep social distance: The linguistic landscape of the major malls in Jeddah amid the COVID-19 pandemic

This study examines the linguistic landscape of the two major malls in Jeddah, Kingdom of Saudi Arabia, through social distancing posters and signs during the COVID-19 pandemic. The study draws on the conceptual framework of linguistic landscape theory, speech acts and semiotics to unveil language dominance, linguistic messages, image-text relations and poster elements that enforce social distancing. A survey questionnaire, primarily aimed at expats, was also administered to find out how they view and interpret the use of bilingual modes in disseminating the social distancing measures. The semiotic analysis reveals that Arabic and English are used in most of the posters, but Arabic remains the dominant language and the preferred medium of information dissemination. Speech acts analysis shows that representatives and directives facilitate implementation of social distancing. The findings also suggest that semiotic modes and signifiers (inscription and materiality) reinforce the effectiveness of the posters. Overall, the use of Arabic and English reflects the country's stance on language policy and economic vision for Jeddah to be a truly global city amid the pandemic.

A Comparative Study on Pandemic Response and Their Impact on Economic Growth: Evidence From COVID-19 Outbreak In Scandanavia

Coronavirus strikes again with the delta variant and puts the world in a phase 3 pandemic state. Countries all over the world have adopted different response mechanisms to contain the virus's spread. Health officials call for lockdown strategies as Covid-19 cases rise in most countries. In a faster and more effective worldwide vaccination scenario, leading economies are racing towards "herd immunity" under an optimistic hypothesis, speeding the world's economic recovery. The justification behind countries making a move towards the open community approach is to keep the economy in good shape. Validating both "lockdown" and "herd immunity" approaches, Scandanavian countries were studied in this paper. Sweden, a Nordic member state that follows an open economy approach, and;Denmark, Finland, and Norway that follows strict social-distancing and lockdown strategies as a measure to flatten the curve were considered in this study. This can help assess each government policy's success or failure against containing the virus. IBM Cognos Business Intelligence platform is used to visualize the different factors affecting the economy namely, the number of infected people and the number of deaths per country. The analysis revealed that Sweden chose an open economy strategy, failed to sustain a stable economy, and continued its upward trajectory with a rising number of virus-related deaths. The comparison of Gross Domestic Product (GDP), inflation, and unemployment rates showed Sweden as one of the least, if not the worst, among other Nordics in flattening the curve. This research thus contradicts the notion of herd immunity as a measure to sustain a healthy economy to be no longer valid. © IEOM Society International.

COVID-19 information overload: Intolerance of uncertainty moderates the relationship between frequency of internet searching and fear of COVID-19.

The COVID-19 pandemic has led to unprecedented levels of uncertainty for people around the world. Research suggests that internet searching resulting in contradictory information can lead to increased levels of distress, particularly for people who have a high intolerance of uncertainty (IU). In the present correlational study, U.S. undergraduate students (N = 317) indicated their IU, the frequency with which they search for COVID-19 related information online, their overall health anxiety, their fear of COVID-19 (FCV-19), and engagement in prevention behaviors. Consistent with previous research, individual differences in IU moderated the relationship between internet searches and FCV-19 such that for people high in IU, more internet searching was associated with greater fear. In turn, we also found that greater FCV-19 predicted more social-distancing behaviors. These findings are important in both future mental health and public health initiatives.

Impact of COVID-19 public health safety measures on births in Scotland between March and May 2020.

OBJECTIVE: To combat the widespread transmission of COVID-19, many countries, including the United Kingdom, have imposed nationwide lockdowns. Little is known about how these public health safety measures affect pregnant mothers and their offspring. This study aimed to explore the impact of COVID-19 public health safety measures on births in Scotland. STUDY DESIGN: Cross-sectional study. METHODS: Using routinely collected health data on pregnancy and birth in Scotland, this study compares all births (N = 7342) between 24th March and May 2020 with births in the same period in 2018 (N = 8323) to investigate the potential negative impact of public health safety measures introduced in Scotland in spring 2020. Birth outcomes were compared using Mann-Whitney-U tests and chi-square tests. RESULTS: Mothers giving birth during the pandemic tended to combine breastfeeding and formula-feeding rather than exclusively breastfeed or exclusively formula-feed, stayed in hospital for fewer days, and more often had an epidural or a spinal anaesthetic compared to women giving birth in 2018. CONCLUSION: Overall, results suggest little impact of public health safety measures on birth outcomes. Further research is needed to explore the longer-term impacts of being born in the pandemic on both maternal mental health and child development.

Examining the effects of the COVID-19 pandemic on community engagement for people with mobility disabilities.

BACKGROUND: The COVID-19 pandemic and subsequent mandates upended community participation in the United States. People with disabilities were often more vulnerable to the adverse effects of the pandemic. Some areas of community participation affected for this population include employment, access to transportation, and social engagement and connection to others. OBJECTIVES: The purpose of this study was to explore the effects of the COVID-19 pandemic for people with mobility disabilities across a variety of topics related to community engagement including social interactions with family and friends, and access to caregivers, groceries, transportation, and employment. METHODS: A survey was administered to participants with mobility disabilities (N = 39). Participants were asked to elaborate on topic areas that they identified as being affected by the COVID-19 pandemic. Data analysis included descriptive statistics and a content analysis in search of themes from open-ended responses. RESULTS: Results indicate that access to family and friends was the most negatively affected topic related to participation, followed by access to food and groceries, transportation, employment, living independently, caring for others, and participating in the community in general. In response to these pandemic-related challenges, participants reported utilizing technology to connect with others and to get essential items delivered. CONCLUSIONS: Findings from this rapid research emphasize the need for emergency preparedness strategies, accessible and reliable resources related to technology use (e.g., Internet), and continued access to services for people with disabilities to maintain various aspects of community participation throughout the COVID-19 pandemic and in the future.

Toward Achieving a Vaccine-Derived Herd Immunity Threshold for COVID-19 in the U.S.

A novel coronavirus emerged in December of 2019 (COVID-19), causing a pandemic that inflicted unprecedented public health and economic burden in all nooks and corners of the world. Although the control of COVID-19 largely focused on the use of basic public health measures (primarily based on using non-pharmaceutical interventions, such as quarantine, isolation, social-distancing, face mask usage, and community lockdowns) initially, three safe and highly-effective vaccines (by AstraZeneca Inc., Moderna Inc., and Pfizer Inc.), were approved for use in humans in December 2020. We present a new mathematical model for assessing the population-level impact of these vaccines on curtailing the burden of COVID-19. The model stratifies the total population into two subgroups, based on whether or not they habitually wear face mask in public. The resulting multigroup model, which takes the form of a deterministic system of nonlinear differential equations, is fitted and parameterized using COVID-19 cumulative mortality data for the third wave of the COVID-19 pandemic in the United States. Conditions for the asymptotic stability of the associated disease-free equilibrium, as well as an expression for the vaccine-derived herd immunity threshold, are rigorously derived. Numerical simulations of the model show that the size of the initial proportion of individuals in the mask-wearing group, together with positive change in behavior from the non-mask wearing group (as well as those in the mask-wearing group, who do not abandon their mask-wearing habit) play a crucial role in effectively curtailing the COVID-19 pandemic in the United States. This study further shows that the prospect of achieving vaccine-derived herd immunity (required for COVID-19 elimination) in the U.S., using the Pfizer or Moderna vaccine, is quite promising. In particular, our study shows that herd immunity can be achieved in the U.S. if at least 60% of the population are fully vaccinated. Furthermore, the prospect of eliminating the pandemic in the U.S. in the year 2021 is significantly enhanced if the vaccination program is complemented with non-pharmaceutical interventions at moderate increased levels of compliance (in relation to their baseline compliance). The study further suggests that, while the waning of natural and vaccine-derived immunity against COVID-19 induces only a marginal increase in the burden and projected time-to-elimination of the pandemic, adding the impacts of therapeutic benefits of the vaccines into the model resulted in a dramatic reduction in the burden and time-to-elimination of the pandemic.

Social-distancing fatigue: Evidence from real-time crowd-sourced traffic data.

INTRODUCTION: To mitigate the COVID-19 pandemic and prevent overwhelming the healthcare system, social-distancing policies such as school closure, stay-at-home orders, and indoor dining closure have been utilized worldwide. These policies function by reducing the rate of close contact within populations and result in decreased human mobility. Adherence to social distancing can substantially reduce disease spread. Thus, quantifying human mobility and social-distancing compliance, especially at high temporal resolution, can provide great insight into the impact of social distancing policies. METHODS: We used the movement of individuals around New York City (NYC), measured via traffic levels, as a proxy for human mobility and the impact of social-distancing policies (i.e., work from home policies, school closure, indoor dining closure etc.). By data mining Google traffic in real-time, and applying image processing, we derived high resolution time series of traffic in NYC. We used time series decomposition and generalized additive models to quantify changes in rush hour/non-rush hour, and weekday/weekend traffic, pre-pandemic and following the roll-out of multiple social distancing interventions. RESULTS: Mobility decreased sharply on March 14, 2020 following declaration of the pandemic. However, levels began rebounding by approximately April 13, almost 2 months before stay-at-home orders were lifted, indicating premature increase in mobility, which we term social-distancing fatigue. We also observed large impacts on diurnal traffic congestion, such that the pre-pandemic bi-modal weekday congestion representing morning and evening rush hour was dramatically altered. By September, traffic congestion rebounded to approximately 75% of pre-pandemic levels. CONCLUSION: Using crowd-sourced traffic congestion data, we described changes in mobility in Manhattan, NYC, during the COVID-19 pandemic. These data can be used to inform human mobility changes during the current pandemic, in planning for responses to future pandemics, and in understanding the potential impact of large-scale traffic interventions such as congestion pricing policies.

Covid-19 Social Distancing Interventions by Statutory Mandate and Their Observational Correlation to Mortality in the United States and Europe.

PURPOSE: Evaluate the correlation between statutory social distancing interventions and Covid-19 mortality independently in both the United States and Europe. The study is presented as a potential methodology to evaluate the effectiveness of statutory social distancing policy. PATIENTS AND METHODS: Twenty-seven states in the United States and, separately, 12 European countries were selected which had clearly defined and dated establishment of statewide or national mandates for social distancing measures from the Institute for Health Metrics and Evaluation (IHME) data. Mandated social distancing measures considered in this study include: School closures, Prohibition on mass gatherings, business closures, stay at home orders, severe travel restrictions, and closure of non-essential businesses. The state/country Covid-19 peak mortality rate (PMR) was defined as the initial averaged normalized maximum during which social distancing mandates were in effect. Mandate-days were defined as the total days legislative mandates were in place to the PMR. RESULTS: The normalized peak mortality rate in the US and in Europe did not demonstrate a statistically significant correlation to the total mandate days (R-squared=0.053, p=0.246, R-squared=2.4E-06, p=0.996). A significant correlation was found between normalized mortality rate and state/country population density (R-squared=0.524, p=0.00002,R-squared=0.397, p=0.0281). DISCUSSION: The analysis appears to suggest no mandate effective reduction in Covid-19 mortality rate to its defined initial peak when interpreting their mean-effect. A strong correlation to population density suggests human interaction frequency does affect the peak mortality rate.

Compliance and Self-Reporting During the COVID-19 Pandemic: A Cross-Cultural Study of Trust and Self-Conscious Emotions in the United States, Italy, and South Korea.

The coronavirus COVID-19 pandemic is an unprecedented health crisis. Many governments around the world have responded by implementing lockdown measures of various degrees of intensity. To be effective, these measures must rely on citizens' cooperation. In the present study, we drew samples from the United States (N = 597), Italy (N = 606), and South Korea (N = 693) and examined predictors of compliance with social distancing and intentions to report the infection to both authorities and acquaintances. Data were collected between April 6th and 8th 2020. We investigated the role of cultural orientations of horizontal and vertical individualism and collectivism, self-conscious emotions of shame and guilt related to the infection and trust in the government's action. Across all countries, vertical collectivism (VC) predicted stronger shame, whereas horizontal collectivism predicted stronger trust in the government. Only in the United States, VC was associated with stronger trust. Stronger feelings of shame predicted lower compliance and intentions to report the infection to both authorities and acquaintances. In contrast, guilt was associated with stronger intentions to report the infection to the authorities. Finally, trust was associated with stronger compliance and intentions to report the infection to the authorities. Unlike Italy and South Korea, the association between trust on compliance was not statistically significant in the United States, implications of the findings, and directions for future research are discussed.

Slowing the spread of COVID-19: Review of "Social distancing" interventions deployed by public transit in the United States and Canada.

This paper presents a review of social distancing measures deployed by transit agencies in the United States and Canada during the COVID-19 pandemic and discusses how specific operators across the two countries have implemented changes. Challenges and impacts on their operations are also provided. Social distancing is one of the community mitigation measures traditionally implemented during influenza pandemics and the novel coronavirus pandemic. Research has shown that social distancing is effective in containing the spread of disease. This is applicable to the current situation with the novel coronavirus, given the lack of effective vaccines and treatments in the United States and Canada in the first eight months of the pandemic. Moreover, social distancing is particularly useful in settings where community transmission is substantial. Directives for social distancing were issued in several states and public transit operators were charged with how to provide for physical distance of six feet between passengers on their property including physical infrastructure such as station buildings and rolling infrastructure (rolling stock) including trains, subway cars and buses. Operational changes were also required due to physical distancing, e.g. adding train cars to provide for opportunities to physically distance on the train. Examples of some measures discussed in this research includes taping off every other seat on buses, increasing the total length of trains by adding cars, separating bus drivers from passengers with plastic sheeting, rear door boarding, etc. This research also analyzes long-term impacts for transit operators and challenges to encourage passengers to return to public transit after lockdown requirements ordered by government officials are lifted. A section on the policies that are being explored by government to continue to sustain public transportation is also included.

Human choice to self-isolate in the face of the COVID-19 pandemic: A game dynamic modelling approach.

Non-pharmaceutical interventions (NPIs) involving social-isolation strategies such as self-quarantine (SQ) and social-distancing (SD) are useful in controlling the spread of infections that are transmitted through human-to-human contacts, e.g., respiratory diseases such as COVID-19. In the absence of a safe and effective cure or vaccine during the first ten months of the COVID-19 pandemic, countries around the world implemented these social-isolation strategies and other NPIs to reduce COVID-19 transmission. But, individual and public perception play a crucial role in the success of any social-isolation measure. Thus, in spite of governments' initiatives to use NPIs to combat COVID-19 in many countries around the world, individual choices rendered social-isolation unsuccessful in some of these countries. This resulted in huge outbreaks that imposed a substantial morbidity, mortality, hospitalization, economic, etc., toll on human lives. In particular, human choices pose serious challenges to public health strategic decision-making in controlling the COVID-19 pandemic. To unravel the impact of this behavioral response to social-isolation on the burden of the COVID-19 pandemic, we develop a model framework that integrates COVID-19 transmission dynamics with a multi-strategy evolutionary game approach of individual decision-making. We use this integrated framework to characterize the evolution of human choices in social-isolation as the disease progresses and public health control measures such as mandatory lockdowns are implemented. Analysis of the model illustrates that SD plays a major role in reducing the burden of the disease compared to SQ. Parameter estimation using COVID-19 incidence data, as well as different lockdown data sets from India, and scenario analysis involving a combination of Voluntary-Mandatory implementation of SQ and SD shows that the effectiveness of this approach depends on the type of isolation, and the time and period of implementation of the selected isolation measure during the outbreak.

Adapting inpatient addiction medicine consult services during the COVID-19 pandemic.

BACKGROUND: We describe addiction consult services (ACS) adaptations implemented during the Novel Coronavirus Disease 2019 (COVID-19) pandemic across four different North American sites: St. Paul's Hospital in Vancouver, British Columbia; Oregon Health & Sciences University in Portland, Oregon; Boston Medical Center in Boston, Massachusetts; and Yale New Haven Hospital in New Haven, Connecticut. EXPERIENCES: ACS made system, treatment, harm reduction, and discharge planning adaptations. System changes included patient visits shifting to primarily telephone-based consultations and ACS leading regional COVID-19 emergency response efforts such as substance use treatment care coordination for people experiencing homelessness in COVID-19 isolation units and regional substance use treatment initiatives. Treatment adaptations included providing longer buprenorphine bridge prescriptions at discharge with telemedicine follow-up appointments and completing benzodiazepine tapers or benzodiazepine alternatives for people with alcohol use disorder who could safely detoxify in outpatient settings. We believe that regulatory changes to buprenorphine, and in Vancouver other medications for opioid use disorder, helped increase engagement for hospitalized patients, as many of the barriers preventing them from accessing care on an ongoing basis were reduced. COVID-19 specific harm reductions recommendations were adopted and disseminated to inpatients. Discharge planning changes included peer mentors and social workers increasing hospital in-reach and discharge outreach for high-risk patients, in some cases providing prepaid cell phones for patients without phones. RECOMMENDATIONS FOR THE FUTURE: We believe that ACS were essential to hospitals' readiness to support patients that have been systematically marginilized during the pandemic. We suggest that hospitals invest in telehealth infrastructure within the hospital, and consider cellphone donations for people without cellphones, to help maintain access to care for vulnerable patients. In addition, we recommend hospital systems evaluate the impact of such interventions. As the economic strain on the healthcare system from COVID-19 threatens the very existence of ACS, overdose deaths continue rising across North America, highlighting the essential nature of these services. We believe it is imperative that health care systems continue investing in hospital-based ACS during public health crises.

Mobility and the effective reproduction rate of COVID-19.

OBJECTIVES: Due to the infectiousness of COVID-19, the mobility of individuals has sharply decreased, both in response to government policy and self-protection. This analysis seeks to understand how mobility reductions reduce the spread of the coronavirus (SAR-CoV-2), using readily available data sources. METHODS: Mobility data from Google is correlated with estimates of the effective reproduction rate, R t , which is a measure of viral infectiousness (Google, 2020). The Google mobility data provides estimates of reductions in mobility, for six types of trips and activities. R t for US states are downloaded from an on-line platform that derives daily estimates based on data from the Covid Tracking Project (Wissel et al., 2020; Systrom et al., 2020). Fixed effects models are estimated relating mean R t and 80% upper level credible interval estimates to changes in mobility and a time-trend value and with both 7-day and 14-day lags. RESULTS: All mobility variables are correlated with median R t and the upper level credible interval of R t . Staying at home is effective at reducing R t, . Time spent at parks has a small positive effect, while other activities all have larger positive effects. The time trend is negative suggesting increases in self-protective behavior. Predictions suggest that returning to baseline levels of activity for retail, transit, and workplaces, will increase R t above 1.0, but not for other activities. Mobility reductions of about 20-40% are needed to achieve an R t below 1.0 (for the upper level 80% credible interval) and even larger reductions to achieve an R t below 0.7. CONCLUSIONS: Policy makers need to be cautious with encouraging return to normal mobility behavior, especially returns to workplaces, transit, and retail locations. Activity at parks appears to not increase R t as much. This research also demonstrates the value of using on-line data sources to conduct rapid policy-relevant analysis of emerging issues.