scholarly journals Human-Network Regions as Effective Geographic Units for Disease Mitigation

2021 ◽  
Author(s):  
Clio Andris ◽  
Caglar Koylu ◽  
Mason A. Porter
Keyword(s):  
United States ◽  
Human Movement ◽  
County Level ◽  
Policy Decisions ◽  
Emergency Situations ◽  
Detection Algorithms ◽  
Functional Regions ◽  
Geographic Boundaries ◽  
Case Rate ◽  
Geographic Regions

Susceptibility to infectious diseases such as COVID-19 depends on how they spread, and many studies have captured the decrease in COVID-19 spread due to reduction in travel. However, less is known about practical geographic boundaries for that limit the spread of COVID-19 to adjacent places. To detect such boundaries, we apply community-detection algorithms to large networks of mobility and social-media connections to construct geographic regions that reflect natural human movement and relationships at the county level for the continental United States. We measure COVID-19 cases, case rates, and case-rate variations across adjacent counties and examine how often COVID-19 crosses the boundaries of these functional regions. We find that regions that we construct using GPS-trace networks and especially commuter networks have the smallest rates of COVID-19 case rates along the boundaries, so these regions may reflect natural partitions in COVID-19 transmission. Conversely, regions that we construct from geolocated Facebook friendships and Twitter connections yield the least effective partitions. Our analysis reveals that regions that are derived from movement flows are more appropriate geographic units than states for making policy decisions about opening areas for activity, assessing vulnerability of populations, and allocating resources. Our insights are also relevant for policy decisions and public messaging in future emergency situations.

scholarly journals Effect of specific non-pharmaceutical intervention policies on SARS-CoV-2 transmission in the counties of the United States

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bingyi Yang ◽  
Angkana T. Huang ◽  
Bernardo Garcia-Carreras ◽  
William E. Hart ◽  
Andrea Staid ◽  
...  
Keyword(s):  
United States ◽  
Home Visiting ◽  
Leisure Activities ◽  
The United States ◽  
Causal Effects ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
County Level ◽  
Metapopulation Model ◽  
Pharmaceutical Interventions

AbstractNon-pharmaceutical interventions (NPIs) remain the only widely available tool for controlling the ongoing SARS-CoV-2 pandemic. We estimated weekly values of the effective basic reproductive number (Reff) using a mechanistic metapopulation model and associated these with county-level characteristics and NPIs in the United States (US). Interventions that included school and leisure activities closure and nursing home visiting bans were all associated with a median Reff below 1 when combined with either stay at home orders (median Reff 0.97, 95% confidence interval (CI) 0.58–1.39) or face masks (median Reff 0.97, 95% CI 0.58–1.39). While direct causal effects of interventions remain unclear, our results suggest that relaxation of some NPIs will need to be counterbalanced by continuation and/or implementation of others.

Developing National Genotype-Independent Indicators for Recent Mycobacterium Tuberculosis Transmission Using Pediatric Cases—United States, 2011-2017

2021 ◽  
pp. 003335492098521
Author(s):  
Alexia V. Harrist ◽  
Clinton J. McDaniel ◽  
Jonathan M. Wortham ◽  
Sandy P. Althomsons
Keyword(s):  
United States ◽  
Mycobacterium Tuberculosis ◽  
Statistical Model ◽  
Moving Average ◽  
The United States ◽  
Tuberculosis Transmission ◽  
Average Proportion ◽  
Pediatric Tb ◽  
Case Rate ◽  
Pediatric Tuberculosis

Introduction Pediatric tuberculosis (TB) cases are sentinel events for Mycobacterium tuberculosis transmission in communities because children, by definition, must have been infected relatively recently. However, these events are not consistently identified by genotype-dependent surveillance alerting methods because many pediatric TB cases are not culture-positive, a prerequisite for genotyping. Methods We developed 3 potential indicators of ongoing TB transmission based on identifying counties in the United States with relatively high pediatric (aged <15 years) TB incidence: (1) a case proportion indicator: an above-average proportion of pediatric TB cases among all TB cases; (2) a case rate indicator: an above-average pediatric TB case rate; and (3) a statistical model indicator: a statistical model based on a significant increase in pediatric TB cases from the previous 8-quarter moving average. Results Of the 249 US counties reporting ≥2 pediatric TB cases during 2009-2017, 240 and 249 counties were identified by the case proportion and case rate indicators, respectively. The statistical model indicator identified 40 counties with a significant increase in the number of pediatric TB cases. We compared results from the 3 indicators with an independently generated list of 91 likely transmission events involving ≥2 pediatric cases (ie, known TB outbreaks or case clusters with reported epidemiologic links). All counties with likely transmission events involving multiple pediatric cases were identified by ≥1 indicator; 23 were identified by all 3 indicators. Practice Implications This retrospective analysis demonstrates the feasibility of using routine TB surveillance data to identify counties where ongoing TB transmission might be occurring, even in the absence of available genotyping data.

scholarly journals Association between county-level social capital and the burden of COVID-19 cases and deaths in the United States

2021 ◽  
Vol 59 ◽  
pp. 21-23
Author(s):  
Mao Yanagisawa ◽  
Ichiro Kawachi ◽  
Christopher A. Scannell ◽  
Carlos Irwin A. Oronce ◽  
Yusuke Tsugawa
Keyword(s):  
United States ◽  
Social Capital ◽  
The United States ◽  
County Level

scholarly journals 1068. Large-Scale Migration and the Changing Viral Hepatitis Prevalences in North America: A modeling approach

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S563-S563
Author(s):  
Kenneth A Valles ◽  
Lewis R Roberts
Keyword(s):  
United States ◽  
Viral Hepatitis ◽  
Large Scale ◽  
Country Of Origin ◽  
Human Movement ◽  
High Volume ◽  
The United States ◽  
The Philippines ◽  
Outcome Data ◽  
Treatment Programs

Abstract Background Infection by hepatitis B and C viruses causes inflammation of the liver and can lead to cirrhosis, liver failure, and hepatocellular carcinoma. The WHO’s ambition to eliminate viral hepatitis by 2030 requires strategies specific to the dynamic disease profiles each nation faces. Large-scale human movement from high-prevalence nations to the United States and Canada have altered the disease landscape, likely warranting adjustments to present elimination approaches. However, the nature and magnitude of the new disease burden remains unknown. This study aims to generate a modeled estimate of recent HBV and HCV prevalence changes to the United States and Canada due to migration. Methods Total migrant populations from 2010-2019 were obtained from United Nations Migrant Stock database. Country-of-origin HBV and HCV prevalences were obtained for the select 40 country-of-origin nations from the Polaris Observatory and systematic reviews. A standard pivot table was used to evaluate the disease contribution from and to each nation. Disease progression estimates were generated using the American Association for the Study of the Liver guidelines and outcome data. Results Between 2010 and 2019, 7,676,937 documented migrants arrived in US and Canada from the selected high-volume nations. Primary migrant source regions were East Asia and Latin America. Combined, an estimated 878,995 migrants were HBV positive, and 226,428 HCV positive. The majority of both migrants (6,477,506) and new viral hepatitis cases (HBV=840,315 and HCV=215,359) were found in the United States. The largest source of HBV cases stemmed from the Philippines, and HCV cases from El Salvador. Conclusion Massive human movement has significantly changed HBV and HCV disease burdens in both the US and Canada over the past decade and the long-term outcomes of cirrhosis and HCC are also expected to increase. These increases are likely to disproportionally impact individuals of the migrant and refugee communities and screening and treatment programs must be strategically adjusted in order to reduce morbidity, mortality, and healthcare expenses. Disclosures All Authors: No reported disclosures

Are spatial models advantageous for predicting county-level HIV epidemiology across the United States?

2021 ◽  
pp. 100436
Author(s):  
Danielle Sass ◽  
Bita Fayaz Farkhad ◽  
Bo Li ◽  
Man-pui Sally Chan ◽  
Dolores Albarracin
Keyword(s):  
United States ◽  
Spatial Models ◽  
The United States ◽  
County Level ◽  
Hiv Epidemiology
Sign in / Sign up

Export Citation Format

Share Document