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1.
J Transl Med ; 20(1): 314, 2022 07 14.
Article in English | MEDLINE | ID: covidwho-1933145

ABSTRACT

BACKGROUND: The outbreak of SARS-CoV-2 continues to pose a serious threat to human health and social. The ongoing pandemic of COVID-19 caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has made a serious threat to public health and economic stability worldwide. Given the urgency of the situation, researchers are attempting to repurpose existing drugs for treating COVID-19. METHODS: We first established an anti-coronavirus drug screening platform based on the Homogeneous Time Resolved Fluorescence (HTRF) technology and the interaction between the coronavirus spike protein and its host receptor ACE2. Two compound libraries of 2,864 molecules were screened with this platform. Selected candidate compounds were validated by SARS-CoV-2_S pseudotyped lentivirus and ACE2-overexpressing cell system. Molecular docking was used to analyze the interaction between S protein and compounds. RESULTS: We identified three potential anti-coronavirus compounds: tannic acid (TA), TS-1276 (anthraquinone), and TS-984 (9-Methoxycanthin-6-one). Our in vitro validation experiments indicated that TS-984 strongly inhibits the interaction of the coronavirus S protein and the human cell ACE2 receptor. Additionally, tannic acid showed moderate inhibitory effect on the interaction of S protein and ACE2. CONCLUSION: This platform is a rapid, sensitive, specific, and high throughput system, and available for screening large compound libraries. TS-984 is a potent blocker of the interaction between the S-protein and ACE2, which might have the potential to be developed into an effective anti-coronavirus drug.


Subject(s)
COVID-19 , Spike Glycoprotein, Coronavirus , Angiotensin-Converting Enzyme 2 , COVID-19/drug therapy , Humans , Molecular Docking Simulation , Peptidyl-Dipeptidase A/metabolism , Protein Binding , SARS-CoV-2 , Spike Glycoprotein, Coronavirus/metabolism , Tannins/metabolism
2.
Int J Appl Earth Obs Geoinf ; 112: 102848, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1895128

ABSTRACT

In response to the coronavirus disease 2019 (COVID-19) pandemic, various countries have sought to control COVID-19 transmission by introducing non-pharmaceutical interventions. Restricting population mobility, by introducing social distancing, is one of the most widely used non-pharmaceutical interventions. Although similar population mobility restriction interventions were introduced, their impacts on COVID-19 transmission are often inconsistent across different regions and different time periods. These differences may provide critical information for tailoring COVID-19 control strategies. In this paper, anonymized high spatiotemporal resolution mobile-phone location data were employed to empirically analyze and quantify the impact of lockdowns on population mobility. Both the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China and the San Francisco Bay Area (SBA) in the United States were studied. In response to the lockdowns, a general reduction in population mobility was observed, but the structural changes in mobility are very different between the two bays: 1) GBA mobility decreased by approximately 74.0-80.1% while the decrease of SBA was about 25.0-42.1%; 2) compared to SBA, the GBA had smoother volatility in daily volume during the lockdown. The volatility change indexes for GBA and SBA were 2.55% and 7.52%, respectively; 3) the effect of lockdown on short- to long-distance mobility was similar in GBA while the medium- and long-distance impact was more pronounced in SBA.

3.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-337797

ABSTRACT

Background: The outbreak of SARS-CoV-2 continues to pose a serious threat to human health and social. The ongoing pandemic of COVID-19 caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has made a serious threat to public health and economic stability worldwide. Given the urgency of the situation, researchers are attempting to repurpose existing drugs for treating COVID-19. Methods We first established an anti-coronavirus drug screening platform based on the Homogeneous Time Resolved Fluorescence (HTRF) technology and the interaction between the coronavirus S protein and its host receptor ACE2. Two compound libraries of 2,864 molecules were screened with this platform. Selected candidate compounds were validated by SARS-CoV-2_S pseudotyped lentivirus and ACE2-overexpressing cell system. Molecular docking was used to analyze the interaction between S-protein and compounds. Results We identified three potential anti-coronavirus compounds: tannic acid (TA), TS-1276 (anthraquinone), and TS-984 (9-Methoxycanthin-6-one). Our in vitro validation experiments indicated that TS-984 strongly inhibits the interaction of the coronavirus S-protein and the human cell ACE2 receptor. Additionally, tannic acid showed moderate inhibitory effect on the interaction of S-protein and ACE2. Conclusion This platform is a rapid, sensitive, specific, and high throughput system, and available for screening large compound libraries. TS-984 is a potent blocker of the interaction between the S-protein and ACE2, which might have the potential to be developed into an effective anti-coronavirus drug.

4.
Trans GIS ; 26(4): 1939-1961, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1752747

ABSTRACT

In this study, we aim to reveal hidden patterns and confounders associated with policy implementation and adherence by investigating the home-dwelling stages from a data-driven perspective via Bayesian inference with weakly informative priors and by examining how home-dwelling stages in the USA varied geographically, using fine-grained, spatial-explicit home-dwelling time records from a multi-scale perspective. At the U.S. national level, two changepoints are identified, with the former corresponding to March 22, 2020 (9 days after the White House declared the National Emergency on March 13) and the latter corresponding to May 17, 2020. Inspections at U.S. state and county level reveal notable spatial disparity in home-dwelling stage-related variables. A pilot study in the Atlanta Metropolitan area at the Census Tract level reveals that the self-quarantine duration and increase in home-dwelling time are strongly correlated with the median household income, echoing existing efforts that document the economic inequity exposed by the U.S. stay-at-home orders. To our best knowledge, our work marks a pioneering effort to explore multi-scale home-dwelling patterns in the USA from a purely data-driven perspective and in a statistically robust manner.

5.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315240

ABSTRACT

The COVID-19 pandemic has profoundly impacted the economy and human lives worldwide, particularly the vulnerable low-income population. We employ a large panel data of 5.6 million daily transactions from 2.6 million debit cards owned by the low-income population in the U.S. to quantify the joint impacts of the state lockdowns and stimulus payments on this population’s spending along the inter-temporal, geo-spatial, and cross-category dimensions. Leveraging difference-in-differences and spatial association analyses at the per card and zip code levels, we uncover three key findings. (1) Inter-temporally, the state lockdowns diminished the daily average spending relative to the same period in 2019 by $3.9 per card and $2,214 per zip code, whereas the stimulus payments elevated the daily average spending by $15.7 per card and $3,307 per zip code. (2) Spatial heterogeneity prevailed: Democratic zip codes displayed much more volatile dynamics, with an initial decline three times that of Republican zip codes followed by a higher rebound and a net gain after the stimulus payments;Southwest exhibited the highest initial decline whereas Southeast largest net gain after the stimulus payments. (3) Across 26 categories, the stimulus payments promoted spending in those categories that enhanced public health and charitable donations, reduced food insecurity and digital divide, while having also stimulated non-essential and even undesirable categories, such as cigar and liquor. Overall, these analyses reveal the imperative need for more geo- and category-targeted stimulus programs to protect and promote the well-being of the low-income population amid the public health and economic crises.

6.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-313736

ABSTRACT

Understanding dynamic human mobility changes and spatial interaction patterns at different geographic scales is crucial for assessing the impacts of non-pharmaceutical interventions (such as stay-at-home orders) during the COVID-19 pandemic. In this data descriptor, we introduce a regularly-updated multiscale dynamic human mobility flow dataset across the United States, with data starting from March 1st, 2020. By analyzing millions of anonymous mobile phone users' visits to various places provided by SafeGraph, the daily and weekly dynamic origin-to-destination (O-D) population flows are computed, aggregated, and inferred at three geographic scales: census tract, county, and state. There is high correlation between our mobility flow dataset and openly available data sources, which shows the reliability of the produced data. Such a high spatiotemporal resolution human mobility flow dataset at different geographic scales over time may help monitor epidemic spreading dynamics, inform public health policy, and deepen our understanding of human behavior changes under the unprecedented public health crisis. This up-to-date O-D flow open data can support many other social sensing and transportation applications.

7.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-310878

ABSTRACT

The emergence of SARS-CoV-2 and the coronavirus infectious disease (COVID-19) has become a pandemic. Social (physical) distancing is a key non-pharmacologic control measure to reduce the transmission rate of SARS-COV-2, but high-level adherence is needed. Using daily travel distance and stay-at-home time derived from large-scale anonymous mobile phone location data provided by Descartes Labs and SafeGraph, we quantify the degree to which social distancing mandates have been followed in the U.S. and its effect on growth of COVID-19 cases. The correlation between the COVID-19 growth rate and travel distance decay rate and dwell time at home change rate was -0.586 (95% CI: -0.742 ~ -0.370) and 0.526 (95% CI: 0.293 ~ 0.700), respectively. Increases in state-specific doubling time of total cases ranged from 1.04 ~ 6.86 days to 3.66 ~ 30.29 days after social distancing orders were put in place, consistent with mechanistic epidemic prediction models. Social distancing mandates reduce the spread of COVID-19 when they are followed.

8.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-310877

ABSTRACT

To contain the Coronavirus disease (COVID-19) pandemic, one of the non-pharmacological epidemic control measures in response to the COVID-19 outbreak is reducing the transmission rate of SARS-COV-2 in the population through (physical) social distancing. An interactive web-based mapping platform that provides timely quantitative information on how people in different counties and states reacted to the social distancing guidelines was developed with the support of the National Science Foundation (NSF). It integrates geographic information systems (GIS) and daily updated human mobility statistical patterns derived from large-scale anonymized and aggregated smartphone location big data at the county-level in the United States, and aims to increase risk awareness of the public, support governmental decision-making, and help enhance community responses to the COVID-19 outbreak.

9.
Int J Health Geogr ; 21(1): 1, 2022 01 19.
Article in English | MEDLINE | ID: covidwho-1633795

ABSTRACT

This article provides a state-of-the-art summary of location privacy issues and geoprivacy-preserving methods in public health interventions and health research involving disaggregate geographic data about individuals. Synthetic data generation (from real data using machine learning) is discussed in detail as a promising privacy-preserving approach. To fully achieve their goals, privacy-preserving methods should form part of a wider comprehensive socio-technical framework for the appropriate disclosure, use and dissemination of data containing personal identifiable information. Select highlights are also presented from a related December 2021 AAG (American Association of Geographers) webinar that explored ethical and other issues surrounding the use of geospatial data to address public health issues during challenging crises, such as the COVID-19 pandemic.


Subject(s)
COVID-19 , Privacy , Confidentiality , Humans , Pandemics , Public Health , SARS-CoV-2 , Social Justice
10.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-296795

ABSTRACT

The outbreak of SARS-CoV-2 continues to pose a serious threat to human health and social and economic stability. In this study, we established an anti-coronavirus drug screening platform based on the Homogeneous Time Resolved Fluorescence (HTRF) technology and the interaction between the coronavirus S protein and its host receptor ACE2. This platform is a rapid, sensitive, specific, and high throughput system. With this platform, we screened two compound libraries of 2,864 molecules and identified three potential anti-coronavirus compounds: tannic acid (TA), TS-1276 (anthraquinone), and TS-984 (9-Methoxycanthin-6-one). Our in vitro validation experiments indicated that TS-984 strongly inhibits the interaction of the coronavirus S-protein and the human cell ACE2 receptor. This data suggests that TS-984 is a potent blocker of the interaction between the S-protein and ACE2, which might have the potential to be developed into an effective anti-coronavirus drug.

11.
PLoS One ; 16(9): e0256407, 2021.
Article in English | MEDLINE | ID: covidwho-1398933

ABSTRACT

The COVID-19 pandemic has profoundly impacted the economy and human lives worldwide, particularly the vulnerable low-income population. We employ a large panel data of 5.6 million daily transactions from 2.6 million debit cards owned by the low-income population in the U.S. to quantify the joint impacts of the state lockdowns and stimulus payments on this population's spending along the inter-temporal, geo-spatial, and cross-categorical dimensions. Leveraging the difference-in-differences analyses at the per card and zip code levels, we uncover three key findings. (1) Inter-temporally, the state lockdowns diminished the daily average spending relative to the same period in 2019 by $3.9 per card and $2,214 per zip code, whereas the stimulus payments elevated the daily average spending by $15.7 per card and $3,307 per zip code. (2) Spatial heterogeneity prevailed: Democratic zip codes displayed much more volatile dynamics, with an initial decline three times that of Republican zip codes, followed by a higher rebound and a net gain after the stimulus payments; also, Southwest exhibited the highest initial decline whereas Southeast had the largest net gain after the stimulus payments. (3) Across 26 categories, the stimulus payments promoted spending in those categories that enhanced public health and charitable donations, reduced food insecurity and digital divide, while having also stimulated non-essential and even undesirable categories, such as liquor and cigar. In addition, spatial association analysis was employed to identify spatial dependency and local hot spots of spending changes at the county level. Overall, these analyses reveal the imperative need for more geo- and category-targeted stimulus programs, as well as more effective and strategic policy communications, to protect and promote the well-being of the low-income population during public health and economic crises.


Subject(s)
COVID-19/economics , Pandemics/economics , Poverty/economics , Health Expenditures , Humans , Physical Distancing , SARS-CoV-2/pathogenicity , United States
12.
Front Pharmacol ; 12: 680674, 2021.
Article in English | MEDLINE | ID: covidwho-1389232

ABSTRACT

Liquorice is a traditional medicine. Triterpenoids such as glycyrrhizin and glycyrrhetinic acid are the main active constituents of liquorice. Studies have revealed that these compounds exert inhibitory effects on several viruses, including SARS-CoV-2. The main mechanisms of action of these compounds include inhibition of virus replication, direct inactivation of viruses, inhibition of inflammation mediated by HMGB1/TLR4, inhibition of ß-chemokines, reduction in the binding of HMGB1 to DNA to weaken the activity of viruses, and inhibition of reactive oxygen species formation. We herein review the research progress on the antiviral effects of glycyrrhizin and its derivatives. In addition, we emphasise the significance of exploring unknown antiviral mechanisms, structural modifications, and drug combinations in future studies.

13.
J Proteomics ; 248: 104354, 2021 09 30.
Article in English | MEDLINE | ID: covidwho-1364279

ABSTRACT

Porcine rotavirus (PoRV), particularly group A, is one of the most important swine pathogens, causing substantial economic losses in the animal husbandry industry. To improve understanding of host responses to PoRV infection, we applied isobaric tags for relative and absolute quantification (iTRAQ) labeling coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to quantitatively identify the differentially expressed proteins in PoRV-infected IPEC-J2 cells and confirmed the differentially accumulated proteins (DAPs) expression differences by performing RT-qPCR and Western blot analysis. Herein, in PoRV- and mock-infected IPEC-J2 cells, relative quantitative data were identified for 4724 proteins, 223 of which were DAPs (125 up-accumulated and 98 down-accumulated). Bioinformatics analyses further revealed that a majority of the DAPs are involved in numerous crucial biological processes and signaling pathways, such as metabolic process, immune system process, amino acid metabolism, energy metabolism, immune system, MHC class I peptide loading complex, Hippo signaling pathway, Th1 and Th2 cell differentiation, antigen processing and presentation, and tubule bicarbonate reclamation. The cellular localization prediction analysis indicated that these DAPs may be located in the Golgi apparatus, nucleus, peroxisomal, cytoplasm, mitochondria, extracellular, plasma membrane, and endoplasmic reticulum (ER). Expression levels of three up-accumulated (VAMP4, IKBKE, and TJP3) or two down-accumulated (SOD3 and DHX9) DAPs upon PoRV infection, were further validated by RT-qPCR and Western blot analysis. Collectively, this work is the first time to investigate the protein profile of PoRV-infected IPEC-J2 cells using quantitative proteomics; these findings provide valuable information to better understand the mechanisms underlying the host responses to PoRV infection in piglets. SIGNIFICANCE: The proteomics analysis of this study uncovered the target associated with PoRV-induced innate immune response or cellular damage, and provided relevant insights into the molecular functions, biological processes, and signaling pathway in these targets. Out of these 223 DAPs, the expression levels of three up-accumulated (VAMP4, IKBKE, and TJP3) and two down-accumulated (SOD3 and DHX9) DAPs upon PoRV infection, have been further validated using RT-qPCR and Western blot analysis. These outcomes could uncover how PoRV manipulated the cellular machinery, which could further our understanding of PoRV pathogenesis in piglets.


Subject(s)
Proteome , Rotavirus , Animals , Cell Line , Chromatography, Liquid , Epithelial Cells , Swine , Tandem Mass Spectrometry
14.
Proc Natl Acad Sci U S A ; 118(31)2021 08 03.
Article in English | MEDLINE | ID: covidwho-1319070

ABSTRACT

Since its outbreak in December 2019, the novel coronavirus 2019 (COVID-19) has spread to 191 countries and caused millions of deaths. Many countries have experienced multiple epidemic waves and faced containment pressures from both domestic and international transmission. In this study, we conduct a multiscale geographic analysis of the spread of COVID-19 in a policy-influenced dynamic network to quantify COVID-19 importation risk under different policy scenarios using evidence from China. Our spatial dynamic panel data (SDPD) model explicitly distinguishes the effects of travel flows from the effects of transmissibility within cities, across cities, and across national borders. We find that within-city transmission was the dominant transmission mechanism in China at the beginning of the outbreak and that all domestic transmission mechanisms were muted or significantly weakened before importation posed a threat. We identify effective containment policies by matching the change points of domestic and importation transmissibility parameters to the timing of various interventions. Our simulations suggest that importation risk is limited when domestic transmission is under control, but that cumulative cases would have been almost 13 times higher if domestic transmissibility had resurged to its precontainment level after importation and 32 times higher if domestic transmissibility had remained at its precontainment level since the outbreak. Our findings provide practical insights into infectious disease containment and call for collaborative and coordinated global suppression efforts.


Subject(s)
COVID-19/transmission , Communicable Diseases, Imported/transmission , COVID-19/epidemiology , COVID-19/prevention & control , China/epidemiology , Cities , Communicable Disease Control/legislation & jurisprudence , Communicable Diseases, Imported/epidemiology , Communicable Diseases, Imported/prevention & control , Humans , Models, Statistical , Risk , SARS-CoV-2 , Spatio-Temporal Analysis , Travel
15.
Front Cell Infect Microbiol ; 11: 680728, 2021.
Article in English | MEDLINE | ID: covidwho-1268238

ABSTRACT

The pandemic of COVID-19 caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has led to more than 117 million reported cases and 2.6 million deaths. Accurate diagnosis technologies are vital for controlling this pandemic. Reverse transcription (RT)-based nucleic acid detection assays have been developed, but the strict sample processing requirement of RT has posed obstacles on wider applications. This study established a ligation and recombinase polymerase amplification (L/RPA) combined assay for rapid detection of SARS-CoV-2 on genes N and ORF1ab targeting the specific biomarkers recommended by the China CDC. Ligase-based strategies usually have a low-efficiency problem on RNA templates. This study has addressed this problem by using a high concentration of the T4 DNA ligase and exploiting the high sensitivity of RPA. Through selection of the ligation probes and optimization of the RPA primers, the assay achieved a satisfactory sensitivity of 101 viral RNA copies per reaction, which was comparable to RT-quantitative polymerase chain reaction (RT-qPCR) and other nucleic acid detection assays for SARS-CoV-2. The assay could be finished in less than 30 min with a simple procedure, in which the requirement for sophisticated thermocycling equipment had been avoided. In addition, it avoided the RT procedure and could potentially ease the requirement for sample processing. Once validated with clinical samples, the L/RPA assay would increase the practical testing availability of SARS-CoV-2. Moreover, the principle of L/RPA has an application potential to the identification of concerned mutations of the virus.


Subject(s)
COVID-19 , Recombinases , China , Humans , Nucleic Acid Amplification Techniques , RNA, Viral/genetics , SARS-CoV-2 , Sensitivity and Specificity
17.
Proc Natl Acad Sci U S A ; 118(24)2021 06 15.
Article in English | MEDLINE | ID: covidwho-1246475

ABSTRACT

The COVID-19 pandemic is a global threat presenting health, economic, and social challenges that continue to escalate. Metapopulation epidemic modeling studies in the susceptible-exposed-infectious-removed (SEIR) style have played important roles in informing public health policy making to mitigate the spread of COVID-19. These models typically rely on a key assumption on the homogeneity of the population. This assumption certainly cannot be expected to hold true in real situations; various geographic, socioeconomic, and cultural environments affect the behaviors that drive the spread of COVID-19 in different communities. What's more, variation of intracounty environments creates spatial heterogeneity of transmission in different regions. To address this issue, we develop a human mobility flow-augmented stochastic SEIR-style epidemic modeling framework with the ability to distinguish different regions and their corresponding behaviors. This modeling framework is then combined with data assimilation and machine learning techniques to reconstruct the historical growth trajectories of COVID-19 confirmed cases in two counties in Wisconsin. The associations between the spread of COVID-19 and business foot traffic, race and ethnicity, and age structure are then investigated. The results reveal that, in a college town (Dane County), the most important heterogeneity is age structure, while, in a large city area (Milwaukee County), racial and ethnic heterogeneity becomes more apparent. Scenario studies further indicate a strong response of the spread rate to various reopening policies, which suggests that policy makers may need to take these heterogeneities into account very carefully when designing policies for mitigating the ongoing spread of COVID-19 and reopening.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Human Migration , Models, Biological , Pandemics , SARS-CoV-2 , Cities/epidemiology , Humans , Wisconsin/epidemiology
18.
Algal Res ; 57: 102331, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1233350

ABSTRACT

Viruses are abiotic obligate parasites utilizing complex mechanisms to hijack cellular machinery and reproduce, causing multiple harmful effects in the process. Viruses represent a growing global health concern; at the time of writing, COVID-19 has killed at least two million people around the world and devastated global economies. Lingering concern regarding the virus' prevalence yet hampers return to normalcy. While catastrophic in and of itself, COVID-19 further heralds in a new era of human-disease interaction characterized by the emergence of novel viruses from natural sources with heretofore unseen frequency. Due to deforestation, population growth, and climate change, we are encountering more viruses that can infect larger groups of people with greater ease and increasingly severe outcomes. The devastation of COVID-19 and forecasts of future human/disease interactions call for a creative reconsideration of global response to infectious disease. There is an urgent need for accessible, cost-effective antiviral (AV) drugs that can be mass-produced and widely distributed to large populations. Development of AV drugs should be informed by a thorough understanding of viral structure and function as well as human biology. To maximize efficacy, minimize cost, and reduce development of drug-resistance, these drugs would ideally operate through a varied set of mechanisms at multiple stages throughout the course of infection. Due to their abundance and diversity, natural compounds are ideal for such comprehensive therapeutic interventions. Promising sources of such drugs are found throughout nature; especially remarkable are the algae, a polyphyletic grouping of phototrophs that produce diverse bioactive compounds. While not much literature has been published on the subject, studies have shown that these compounds exert antiviral effects at different stages of viral pathogenesis. In this review, we follow the course of viral infection in the human body and evaluate the AV effects of algae-derived compounds at each stage. Specifically, we examine the AV activities of algae-derived compounds at the entry of viruses into the body, transport through the body via the lymph and blood, infection of target cells, and immune response. We discuss what is known about algae-derived compounds that may interfere with the infection pathways of SARS-CoV-2; and review which algae are promising sources for AV agents or AV precursors that, with further investigation, may yield life-saving drugs due to their diversity of mechanisms and exceptional pharmaceutical potential.

19.
SSRN; 2020.
Preprint | SSRN | ID: ppcovidwho-4372

ABSTRACT

The COVID-19 pandemic has profoundly impacted human behaviour worldwide. Grounded on economic and consumer behavioural theories, we employ a population-scale panel of debit card transaction data to quantify the conjoint impacts of statewide lockdowns and stimulus payments on the dynamic spending patterns of the vulnerable lower-income population in the U.S. Leveraging a difference-in-differences analysis framework, we find that compared to the same period in 2019, the daily spending on average declined by about $3.9 per card and $2,214 per zip code between March 19 and April 11 with the state lockdowns. After the stimulus payments were issued, the daily spending on average increased by about $15.7 per card and $3,307 per zip code between April 11 and May 3. We also demonstrate the partisan difference and geographic heterogeneity in these spending changes. Although having also stimulated less essential categories, the stimulus payments played a crucial role in enhancing public health, resolving food insecurity, increasing charitable donations, and reducing digital divide.

20.
Sci Rep ; 10(1): 22429, 2020 12 30.
Article in English | MEDLINE | ID: covidwho-1003318

ABSTRACT

Most models of the COVID-19 pandemic in the United States do not consider geographic variation and spatial interaction. In this research, we developed a travel-network-based susceptible-exposed-infectious-removed (SEIR) mathematical compartmental model system that characterizes infections by state and incorporates inflows and outflows of interstate travelers. Modeling reveals that curbing interstate travel when the disease is already widespread will make little difference. Meanwhile, increased testing capacity (facilitating early identification of infected people and quick isolation) and strict social-distancing and self-quarantine rules are most effective in abating the outbreak. The modeling has also produced state-specific information. For example, for New York and Michigan, isolation of persons exposed to the virus needs to be imposed within 2 days to prevent a broad outbreak, whereas for other states this period can be 3.6 days. This model could be used to determine resources needed before safely lifting state policies on social distancing.


Subject(s)
COVID-19 Testing/methods , COVID-19/prevention & control , COVID-19/transmission , Communicable Disease Control/methods , Primary Prevention/methods , COVID-19/diagnosis , Forecasting , Geography , Humans , Models, Theoretical , Quarantine , SARS-CoV-2 , Travel , United States
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