scholarly journals Geographic Disparities and Determinants of COVID-19 Incidence Risk in the Greater St. Louis Area, Missouri

2021 ◽  
Author(s):  
Praachi Das ◽  
Morganne Igoe ◽  
Suzanne Lenhart ◽  
Lan Luong ◽  
Cristina Lanzas ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Demographic Data ◽  
Geographic Location ◽  
Sociodemographic Factors ◽  
Population Characteristics ◽  
Population Mobility ◽  
Population Movements ◽  
Geographic Disparities ◽  
Mobility Data ◽  
Per Capita

Background: Evidence suggests that the risk of Coronavirus Disease 2019 (COVID-19) varies geographically due to differences in population characteristics. Therefore, the objectives of this study were to identify: (a) geographic disparities of COVID-19 risk in the Greater St. Louis area of Missouri, USA; (b) predictors of the identified disparities. Methods: Data on COVID-19 incidence and chronic disease hospitalizations were obtained from the Departments of Health and Missouri Hospital Association, respectively. Socioeconomic and demographic data were obtained from the 2018 American Community Survey while population mobility data were obtained from the SafeGraph website. Choropleth maps were used to identify geographic disparities of COVID-19 risk and its predictors at the ZIP Code Tabulation Area (ZCTA) spatial scale. Global negative binomial and local geographically weighted negative binomial models were used to identify predictors of ZCTA-level geographic disparities of COVID-19 risk. Results: There were geographic disparities in COVID-19 risk. Risks tended to be higher in ZCTAs with high percentages of the population with a bachelors degree (p<0.0001) and obesity hospitalizations (p<0.0001). Conversely, risks tended to be lower in ZCTAs with high percentages of the population working in agriculture (p<0.0001). However, the association between agricultural occupation and COVID-19 risk was modified by per capita between ZCTA visits. Areas that had both high per capita between ZCTA visits and high percentages of the population employed in agriculture had high COVID-19 risks. The strength of association between agricultural occupation and COVID-19 risk varied by geographic location. Conclusions: Geographic Information Systems, global and local models are useful for identifying geographic disparities and predictors of COVID-19 risk. Geographic disparities of COVID-19 risk exist in the St. Louis area and are explained by differences in sociodemographic factors, population movements, and obesity hospitalization risks. The latter is particularly concerning due to the growing prevalence of obesity and the known immunological impairments among obese individuals. Therefore, future studies need to focus on improving our understanding of the relationships between COVID-19 vaccination efficacy, obesity and waning of immunity among obese individuals so as to better guide vaccination regimens, reduce disparities and improve population health for all.

scholarly journals Genomic and mobility data reveal mass population movement as a driver of SARS-CoV-2 dissemination and diversity in Bangladesh

2021 ◽  
Author(s):  
Lauren A. Cowley ◽  
Mokibul Hassan Afrad ◽  
Sadia Isfat Ara Rahman ◽  
Md. Mahfuz-Al-Mamun ◽  
Taylor Chin ◽  
...  
Keyword(s):  
Data Streams ◽  
Rural Areas ◽  
Genomic Data ◽  
Mass Vaccination ◽  
Population Mobility ◽  
Population Movements ◽  
Mobility Data ◽  
Mass Migration ◽  
The World ◽  
Vaccination Campaigns

AbstractBackgroundNew data streams are being used to track the pandemic of SARS-CoV-2, including genomic data which provides insights into patterns of importation and spatial spread of the virus, as well as population mobility data obtained from mobile phones. Here, we analyse the emergence and outbreak trajectory of SARS-CoV-2 in Bangladesh using these new data streams, and identify mass population movements as a key early event driving the ongoing epidemic.MethodsWe sequenced complete genomes of 67 SARS-CoV-2 samples (March-July 2020) and combined this dataset with 324 genomes from Bangladesh. For phylogenetic context, we also used 68,000 GISAID genomes collected globally. We paired this genomic data with population mobility information from Facebook and three mobile phone operators.FindingsThe majority (85%) of the Bangladeshi sequenced isolates fall into either pangolin lineage B.1.36 (8%), B.1.1 (19%) or B.1.1.25 (58%). Bayesian time-scaled phylogenetic analysis predicted SARS-COV-2 first appeared in mid-February, through international introductions. The first case was reported on March 8th. This pattern of repeated international introduction changed at the end of March when three discrete lineages expanded and spread clonally across Bangladesh. The shifting pattern of viral diversity across Bangladesh is reflected in the mobility data which shows the mass migration of people from cities to rural areas at the end of March, followed by frequent travel between Dhaka and the rest of the country during the following months.InterpretationIn Bangladesh, population mobility out of Dhaka as well as frequent travel from urban hotspots to rural areas resulted in rapid country-wide dissemination of SARS-CoV-2. The strains in Bangladesh reflect the local expansion of global lineages introduced early from international travellers to and from major international travel hubs. Importantly, the Bangladeshi context is consistent with epidemiologic and phylogenetic findings globally. Bangladesh is one of the few countries in the world with a rich history of conducting mass vaccination campaigns under complex circumstances. Combining genomics and these new data streams should allow population movements to be modelled and anticipated rendering Bangladesh extremely well prepared to immunize citizens rapidly. Based on our genomics data and the country’s successful immunization history, vaccines becoming available globally will be suitable for implementation in Bangladesh while ongoing genomic surveillance is conducted to monitor for new variants of the virus.FundingGovernment of Bangladesh, Bill and Melinda Gates Foundation, Wellcome Trust.Research in contextEvidence before this studyThe emergence of SARS-CoV-2, leading to the COVID-19 pandemic, has motivated all countries in the world to obtain high resolution data on the virus. Globally over 300,000 strains have been sequenced and information made available in GISAID. Within the first 100 days of the emergence of SARS-CoV-2, genomic analysis from different countries led to the development of vaccines which have now reached market. Information on the prevailing genotypes of SARS-CoV-2 since introduction is needed in low and middle-income countries (LMICs), including Bangladesh, in order to determine the suitability of therapeutics and vaccines in the pipeline and help vaccine deployment.Added value of this studyWe sequenced SARS-CoV-2 genomes from strains that were prospectively collected during the height of the pandemic and combined these genomic data with mobility data to comprehensively describe i) how repeated international importations of SARS-CoV-2 were ultimately linked to nationwide spread, ii) 85% of strains belonged to the Pangolin lineages B.1.1, B.1.1.25 and B.1.36 and that similar mutation rates were observed as seen globally iii) the switch in genomic dynamics of SARS-CoV-2 coincided with mass migration out of cities to the rest of the country. We have assessed the contributions of population mobility on the maintenance and spread of clonal lineages of SARS-CoV-2. This is the first time these data types have been combined to look at the spread of this virus nationally.Implications of all the available evidenceSARS-CoV-2 genomic diversity and mutation rate in Bangladesh is comparable to strains circulating globally. Notably, the data on the genomic changes of SARS-CoV-2 in Bangladesh is reassuring, suggesting that immunotherapeutic and vaccines being developed globally should also be suitable for this population. Since Bangladesh already has extensive experience of conducting mass vaccination campaigns, such as the rollout of the oral Cholera vaccine, experience of developing and using new data streams will enable efficient and targeted immunization of the population in 2021 with COVID-19 vaccine(s).

scholarly journals Examining the Economic and Environmental Impacts of COVID-19 Using Earth Observation Data

2020 ◽  
Vol 13 (1) ◽  
pp. 5
Author(s):  
William Straka ◽  
Shobha Kondragunta ◽  
Zigang Wei ◽  
Hai Zhang ◽  
Steven D. Miller ◽  
...  
Keyword(s):  
Air Quality ◽  
Los Angeles ◽  
Environmental Impacts ◽  
Demographic Data ◽  
The United States ◽  
Earth Observation ◽  
Observation Data ◽  
Washington Dc ◽  
Mobility Data ◽  
Earth Observation Data

The COVID-19 pandemic has infected almost 73 million people and is responsible for over 1.63 million fatalities worldwide since early December 2019, when it was first reported in Wuhan, China. In the early stages of the pandemic, social distancing measures, such as lockdown restrictions, were applied in a non-uniform way across the world to reduce the spread of the virus. While such restrictions contributed to flattening the curve in places like Italy, Germany, and South Korea, it plunged the economy in the United States to a level of recession not seen since WWII, while also improving air quality due to the reduced mobility. Using daily Earth observation data (Day/Night Band (DNB) from the National Oceanic and Atmospheric Administration Suomi-NPP and NO2 measurements from the TROPOspheric Monitoring Instrument TROPOMI) along with monthly averaged cell phone derived mobility data, we examined the economic and environmental impacts of lockdowns in Los Angeles, California; Chicago, Illinois; Washington DC from February to April 2020—encompassing the most profound shutdown measures taken in the U.S. The preliminary analysis revealed that the reduction in mobility involved two major observable impacts: (i) improved air quality (a reduction in NO2 and PM2.5 concentration), but (ii) reduced economic activity (a decrease in energy consumption as measured by the radiance from the DNB data) that impacted on gross domestic product, poverty levels, and the unemployment rate. With the continuing rise of COVID-19 cases and declining economic conditions, such knowledge can be combined with unemployment and demographic data to develop policies and strategies for the safe reopening of the economy while preserving our environment and protecting vulnerable populations susceptible to COVID-19 infection.

scholarly journals Is area deprivation associated with greater impacts of COVID-19 in care homes across England? A preliminary analysis of COVID-19 outbreaks and deaths

2021 ◽  
pp. jech-2020-215039 ◽  
Author(s):  
Anders Malthe Bach-Mortensen ◽  
Michelle Degli Esposti
Keyword(s):  
Negative Binomial ◽  
Care Home ◽  
Negative Binomial Regression ◽  
Population Characteristics ◽  
Care Homes ◽  
Future Research ◽  
Area Deprivation ◽  
Binomial Regression ◽  
Index Of Multiple Deprivation

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.

scholarly journals Mobility Patterns in Different Age Groups in Japan during the COVID-19 Pandemic: a Small Area Time Series Analysis through March 2021

2021 ◽  
Author(s):  
Shuhei Nomura ◽  
Yuta Tanoue ◽  
Daisuke Yoneoka ◽  
Stuart Gilmour ◽  
Takayuki Kawashima ◽  
...  
Keyword(s):  
Care Delivery ◽  
Human Mobility ◽  
Age Groups ◽  
Virus Transmission ◽  
Initial Response ◽  
Health Care Delivery System ◽  
Population Characteristics ◽  
Mobility Patterns ◽  
Mobility Data ◽  
The Status

AbstractIn the COVID-19 era, movement restrictions are crucial to slow virus transmission and have been implemented in most parts of the world, including Japan. To find new insights on human mobility and movement restrictions encouraged (but not forced) by the emergency declaration in Japan, we analyzed mobility data at 35 major stations and downtown areas in Japan—each defined as an area overlaid by several 125-meter grids—from September 1, 2019 to March 19, 2021. Data on the total number of unique individuals per hour passing through each area were obtained from Yahoo Japan Corporation (i.e., more than 13,500 data points for each area). We examined the temporal trend in the ratio of the rolling seven-day daily average of the total population to a baseline on January 16, 2020, by ten-year age groups in five time frames. We demonstrated that the degree and trend of mobility decline after the declaration of a state of emergency varies across age groups and even at the subregional level. We demonstrated that monitoring dynamic geographic and temporal mobility information stratified by detailed population characteristics can help guide not only exit strategies from an ongoing emergency declaration, but also initial response strategies before the next possible resurgence. Combining such detailed data with data on vaccination coverage and COVID-19 incidence (including the status of the health care delivery system) can help governments and local authorities develop community-specific mobility restriction policies. This could include strengthening incentives to stay home and raising awareness of cognitive errors that weaken people's resolve to refrain from nonessential movement.

scholarly journals Sickness absence and disability pension after carpal tunnel syndrome diagnosis: A register-based study of patients and matched references in Sweden

2021 ◽  
pp. 140349482110027
Author(s):  
Tea Lallukka ◽  
Rahman Shiri ◽  
Kristina Alexanderson ◽  
Jenni Ervasti ◽  
Ellenor Mittendorfer-Rutz ◽  
...  
Keyword(s):  
Health Care ◽  
Carpal Tunnel Syndrome ◽  
Sickness Absence ◽  
Carpal Tunnel ◽  
Disability Pension ◽  
Negative Binomial ◽  
Age Groups ◽  
Negative Binomial Regression ◽  
Sociodemographic Factors ◽  
Tunnel Syndrome

Aims: The aim of this study was to examine sickness absence and disability pension (SA/DP) during working lifespan among individuals diagnosed with carpal tunnel syndrome (CTS) and their matched references, accounting for sociodemographic factors. Methods: We used a register cohort of 78,040 individuals aged 19–60 years when diagnosed with CTS in secondary health care (hospitals and outpatient specialist health care) and their 390,199 matched references from the general population in 2001–2010. Sociodemographic factors and SA/DP net days during a three-year follow-up were included. Negative binomial regression was used. Results: For those not on DP at inclusion, the average number of SA/DP days per person-year was 58 days (95% confidence interval (CI) 56–60 days) among individuals with CTS and 20 days (95% CI 19–21 days) among the matched references. Among both groups, these numbers increased with age and were higher among women than among men. The rate ratio (RR) of SA/DP days was threefold higher among people with CTS than among the matched references (adjusted RR=3.00, 95% CI 2.91–3.10) Moreover, compared to the matched references, the RR for SA/DP was higher among men with CTS (RR=3.86, 95% CI 3.61–4.13) than among women with CTS (RR=2.69, 95% CI 2.59–2.78). The association between CTS and the number of SA/DP days was smaller among older age groups. Sociodemographic factors were similarly associated with SA/DP among people with and without CTS. Conclusions: Numbers of SA/DP days were higher among people with CTS than their matched references in all age groups, particularly among individuals in their early work careers, highlighting public-health relevance of the findings.

scholarly journals Correlation of age, sex and season with the state of human decomposition as quantified by postmortem computed tomography

2021 ◽  
Author(s):  
Dominic L. C. Guebelin ◽  
Akos Dobay ◽  
Lars Ebert ◽  
Eva Betschart ◽  
Michael J. Thali ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Demographic Data ◽  
Sociodemographic Factors ◽  
The State ◽  
The Body ◽  
Seasonal Effects ◽  
Whole Body ◽  
Postmortem Computed Tomography ◽  
Whole Body Computed Tomography ◽  
Urban Study

AbstractDead bodies exhibit a variable range of changes with advancing decomposition. To quantify intracorporeal gas, the radiological alteration index (RAI) has been implemented in the assessment of postmortem whole-body computed tomography. We used this RAI as a proxy for the state of decomposition. This study aimed to (I) investigate the correlation between the state of decomposition and the season in which the body was discovered; and (II) evaluate the correlations between sociodemographic factors (age, sex) and the state of decomposition, by using the RAI as a proxy for the extent of decomposition. In a retrospective study, we analyzed demographic data from all autopsy reports from the Institute of Forensic Medicine of Zurich between January 2017 to July 2019 and evaluated the radiological alteration index from postmortem whole-body computed tomography for each case. The bodies of older males showed the highest RAI. Seasonal effects had no significant influence on the RAI in our urban study population with bodies mostly being discovered indoors. Autopsy reports contain valuable data that allow interpretation for reasons beyond forensic purposes, such as sociopolitical observations.

scholarly journals Ambient temperature and subsequent COVID-19 mortality in the OECD countries and individual United States

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Costas A. Christophi ◽  
Mercedes Sotos-Prieto ◽  
Fan-Yun Lan ◽  
Mario Delgado-Velandia ◽  
Vasilis Efthymiou ◽  
...  
Keyword(s):  
United States ◽  
Ambient Temperature ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Weather Conditions ◽  
Oecd Countries ◽  
Epidemiological Studies ◽  
Sociodemographic Factors ◽  
Sensitivity Analyses ◽  
Inverse Association

AbstractEpidemiological studies have yielded conflicting results regarding climate and incident SARS-CoV-2 infection, and seasonality of infection rates is debated. Moreover, few studies have focused on COVD-19 deaths. We studied the association of average ambient temperature with subsequent COVID-19 mortality in the OECD countries and the individual United States (US), while accounting for other important meteorological and non-meteorological co-variates. The exposure of interest was average temperature and other weather conditions, measured at 25 days prior and 25 days after the first reported COVID-19 death was collected in the OECD countries and US states. The outcome of interest was cumulative COVID-19 mortality, assessed for each region at 25, 30, 35, and 40 days after the first reported death. Analyses were performed with negative binomial regression and adjusted for other weather conditions, particulate matter, sociodemographic factors, smoking, obesity, ICU beds, and social distancing. A 1 °C increase in ambient temperature was associated with 6% lower COVID-19 mortality at 30 days following the first reported death (multivariate-adjusted mortality rate ratio: 0.94, 95% CI 0.90, 0.99, p = 0.016). The results were robust for COVID-19 mortality at 25, 35 and 40 days after the first death, as well as other sensitivity analyses. The results provide consistent evidence across various models of an inverse association between higher average temperatures and subsequent COVID-19 mortality rates after accounting for other meteorological variables and predictors of SARS-CoV-2 infection or death. This suggests potentially decreased viral transmission in warmer regions and during the summer season.

scholarly journals Modelling Representative Population Mobility for COVID-19 Spatial Transmission in South Africa

2021 ◽  
Vol 4 ◽  
Author(s):  
A. Potgieter ◽  
I. N. Fabris-Rotelli ◽  
Z. Kimmie ◽  
N. Dudeni-Tlhone ◽  
J. P. Holloway ◽  
...  
Keyword(s):  
Human Mobility ◽  
Data Sources ◽  
Population Mobility ◽  
Mobility Patterns ◽  
Mobility Data ◽  
The World ◽  
Spatial Weight ◽  
Data Source ◽  
Reduced Mobility ◽  
Spatial Transmission

The COVID-19 pandemic starting in the first half of 2020 has changed the lives of everyone across the world. Reduced mobility was essential due to it being the largest impact possible against the spread of the little understood SARS-CoV-2 virus. To understand the spread, a comprehension of human mobility patterns is needed. The use of mobility data in modelling is thus essential to capture the intrinsic spread through the population. It is necessary to determine to what extent mobility data sources convey the same message of mobility within a region. This paper compares different mobility data sources by constructing spatial weight matrices at a variety of spatial resolutions and further compares the results through hierarchical clustering. We consider four methods for constructing spatial weight matrices representing mobility between spatial units, taking into account distance between spatial units as well as spatial covariates. This provides insight for the user into which data provides what type of information and in what situations a particular data source is most useful.

scholarly journals The first 100 days of SARS-CoV-2 control in Vietnam

2020 ◽  
Author(s):  
Thai Quang Pham ◽  
Maia Rabaa ◽  
Luong Huy Duong ◽  
Tan Quang Dang ◽  
Quang Dai Tran ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Severe Disease ◽  
Steering Committee ◽  
International Travel ◽  
Control Measures ◽  
Contact Tracing ◽  
Population Mobility ◽  
Early Introduction ◽  
Mobility Data ◽  
Travel Restrictions

Background: One hundred days after SARS-CoV-2 was first reported in Vietnam on January 23rd, 270 cases have been confirmed, with no deaths. We describe the control measures used and their relationship with imported and domestically-acquired case numbers. Methods: Data on the first 270 SARS-CoV-2 infected cases and the timing and nature of control measures were captured by Vietnam's National Steering Committee for COVID-19 response. Apple and Google mobility data provided population movement proxies. Serial intervals were calculated from 33 infector-infectee pairs and used to estimate the proportion of pre-symptomatic transmission events and time-varying reproduction numbers. Results: After the first confirmed case on January 23rd, the Vietnamese Government initiated mass communications measures, contact tracing, mandatory 14-day quarantine, school and university closures, and progressive flight restrictions. A national lockdown was implemented between April 1st and 22nd. Around 200,000 people were quarantined and 266,122 RT-PCR tests conducted. Population mobility decreased progressively before lockdown. 60% (163/270) of cases were imported; 43% (89/208) of resolved infections were asymptomatic. 21 developed severe disease, with no deaths. The serial interval was 3.24 days, and 27.5% (95% confidence interval, 15.7%-40.0%) of transmissions occurred pre-symptomatically. Limited transmission amounted to a maximum reproduction number of 1.15 (95% confidence interval, 0.37-2.36). No community transmission has been detected since April 15th. Conclusions: Vietnam has controlled SARS-CoV-2 spread through the early introduction of communication, contact-tracing, quarantine, and international travel restrictions. The value of these interventions is supported by the high proportion of asymptomatic cases and imported cases, and evidence for substantial pre-symptomatic transmission.

scholarly journals Racial/ethnic and immigrant differences in early childhood diet quality

2013 ◽  
Vol 17 (6) ◽  
pp. 1308-1317 ◽  
Author(s):  
Marieke LA de Hoog ◽  
Ken P Kleinman ◽  
Matthew W Gillman ◽  
Tanja GM Vrijkotte ◽  
Manon van Eijsden ◽  
...  
Keyword(s):  
Fast Food ◽  
Negative Binomial ◽  
Saturated Fat ◽  
Sociodemographic Factors ◽  
Snack Food ◽  
Hispanic Children ◽  
Sugar Sweetened Beverages ◽  
Explanatory Role ◽  
Sweetened Beverages ◽  
Racial Ethnic

AbstractObjectiveTo assess racial/ethnic differences in the diet in young children and the explanatory role of maternal BMI, immigrant status and perception of child's weight.DesignAmong white, black and Hispanic 3-year-olds, we used negative binomial and linear regression to examine associations of race/ethnicity with foods and nutrients assessed by a validated FFQ.SettingProject Viva, Boston (MA), USA.SubjectsChildren aged 3 years (n 898).ResultsMean age was 38·3 (sd 2·8) months; 464 (52 %) were boys and 127 mothers (14 %) were immigrants. After adjustment for sociodemographic factors, black and Hispanic children (v. white) had a higher intake of sugar-sweetened beverages (rate ratio (RR) = 2·59 (95 % CI 1·95, 3·48) and RR = 1·59 (95 % CI 1·07, 2·47), respectively) and lower intakes of skimmed/1 % milk (RR = 0·42 (95 % CI 0·33, 0·53) and RR = 0·43 (95 % CI 0·31, 0·61), respectively) and trans-fat (−0·10 (95 % CI −0·18, −0·03) % of energy and −0·15 (95 % CI −0·26, −0·04) % of energy, respectively). Among Hispanics only, a lower intake of snack food (RR = 0·83 (95 % CI 0·72, 0·98)) was found and among blacks only, a higher intake of fast food (RR = 1·28 (95 % CI 1·05, 1·55)) and lower intakes of saturated fat (−0·86 (95 % CI −1·48, −0·23) % of energy), dietary fibre (0·85 (95 % CI 0·08, 1·62) g/d) and Ca (−120 (95 % CI −175, −65) mg/d) were found. Being born outside the USA was associated with more healthful nutrient intakes and less fast food.ConclusionsThree-year-old black and Hispanic (v. white) children ate more sugar-sweetened beverages and less low-fat dairy. Total energy intake was substantially higher in Hispanic children. Snack food (Hispanic children) and fat intakes (black children) tended to be lower. Children of immigrants ate less fast food and bad fats and more fibre.

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