JUE Insight: Migration, Transportation Infrastructure, and the Spatial Transmission of COVID-19 in China.
Ontology highlight
ABSTRACT:
SUBMITTER: Li B
PROVIDER: S-EPMC8049189 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:This paper investigates the effect of COVID-19 on both housing prices and housing price gradients in China using transaction level data from 60 Chinese cities. After using a difference-in-differences (DID) specification to disentangle the confounding effects of China's annual Spring Festival, we find that housing prices decreased by two percent immediately after the COVID-19 outbreak but gradually recovered by September 2020. Moreover, our findings suggest that COVID-19 flattens the horizontal housing price gradient, reduces the price premium for living in tall buildings, and changes the vertical gradient within residential buildings. This is likely explained by the changing household preferences towards low-density areas associated with lower infection risk.
| S-EPMC9295400 | biostudies-literature
Project description:The evidence on the demographics of COVID-19 fatalities points to an overrepresentation of minorities and an underrepresentation of women. We investigate the joint impact of race and gender using individual-level georeferenced death data collected by the Cook County Medical Examiner, which we structure as a cell-level panel at a race, block group, week, and year level. Through an event study approach, we establish that Black individuals are affected more harshly than White and that the effect is driven by Black women. The Black female bias is associated with occupational segregation in the health care and transportation sectors and by commuting on public transport.
| S-EPMC9272662 | biostudies-literature
Project description:The ongoing pandemic of 2019 novel coronavirus disease (COVID-19) is challenging global public health response system. We aim to identify the risk factors for the transmission of COVID-19 using data on mainland China. We estimated attack rate (AR) at county level. Logistic regression was used to explore the role of transportation in the nationwide spread. Generalized additive model and stratified linear mixed-effects model were developed to identify the effects of multiple meteorological factors on local transmission. The ARs in affected counties ranged from 0.6 to 9750.4 per million persons, with a median of 8.8. The counties being intersected by railways, freeways, national highways or having airports had significantly higher risk for COVID-19 with adjusted odds ratios (ORs) of 1.40 (p = 0.001), 2.07 (p < 0.001), 1.31 (p = 0.04), and 1.70 (p < 0.001), respectively. The higher AR of COVID-19 was significantly associated with lower average temperature, moderate cumulative precipitation and higher wind speed. Significant pairwise interactions were found among above three meteorological factors with higher risk of COVID-19 under low temperature and moderate precipitation. Warm areas can also be in higher risk of the disease with the increasing wind speed. In conclusion, transportation and meteorological factors may play important roles in the transmission of COVID-19 in mainland China, and could be integrated in consideration by public health alarm systems to better prevent the disease.
| S-EPMC7448770 | biostudies-literature
Project description:Due to continuous spread of coronavirus disease 2019 (COVID-19) worldwide, long-term effective prevention and control measures should be adopted for public transport facilities, as they are increasing in popularity and serve as the principal modes for travel of many people. The human infection risk could be extremely high due to length of exposure time window, transmission routes and structural characteristics during travel or work. This can result in the rapid spread of the infection. Based on the transmission characteristics of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and the nature of public transport sites, we identified comprehensive countermeasures toward the prevention and control of COVID-19, including the strengthening of personnel management, personal protection, environmental cleaning and disinfection, and health education. Multi-pronged strategies can enhance safety of public transportation. The prevention and control of the disease during the use of public transportation will be particularly important when all countries in the world resume production. The aim of this study is to introduce experience of the prevention and control measures for public transportation in China to promote the global response to COVID-19.
| S-EPMC7833563 | biostudies-literature
Project description:The international spread of COVID-19 infection has attracted global attention, but the impact of local or domestic travel restriction on public transportation network remains unclear. Passenger volume data for the domestic public transportation network in Japan and the time at which the first confirmed COVID-19 case was observed in each prefecture were extracted from public data sources. A survival approach in which a hazard was modeled as a function of the closeness centrality on the network was utilized to estimate the risk of importation of COVID-19 in each prefecture. A total of 46 prefectures with imported cases were identified. Hypothetical scenario analyses indicated that both strategies of locking down the metropolitan areas and restricting domestic airline travel would be equally effective in reducing the risk of importation of COVID-19. While caution is necessary that the data were limited to June 2020 when the pandemic was in its initial stage and that no other virus spreading routes have been considered, domestic travel restrictions were effective to prevent the spread of COVID-19 on public transportation network in Japan. Instead of lockdown that might seriously damage the economy, milder travel restrictions could have the similar impact on controlling the domestic transmission of COVID-19.
| S-EPMC7862278 | biostudies-literature
Project description:We investigate, through a data-driven contact tracing model, the transmission of COVID-19 inside buses during distinct phases of the pandemic in a large Brazilian city. From this microscopic approach, we recover the networks of close contacts within consecutive time windows. A longitudinal comparison is then performed by upscaling the traced contacts with the transmission computed from a mean-field compartmental model for the entire city. Our results show that the effective reproduction numbers inside the buses, [Formula: see text], and in the city, [Formula: see text], followed a compatible behavior during the first wave of the local outbreak. Moreover, by distinguishing the close contacts of healthcare workers in the buses, we discovered that their transmission, [Formula: see text], during the same period, was systematically higher than [Formula: see text]. This result reinforces the need for special public transportation policies for highly exposed groups of people.
| S-EPMC8712527 | biostudies-literature
Project description:On January 23, 2020, China quarantined Wuhan to contain an emerging coronavirus (COVID-19). We estimated the probability of transportation of COVID-19 from Wuhan to 369 cities in China before the quarantine. The expected risk is >50% in 130 (95% CI 89-190) cities and >99% in the 4 largest metropolitan areas of China.
| S-EPMC7239085 | biostudies-literature
Project description:BACKGROUND:Massive internal migration from rural to urban areas poses new challenges for tuberculosis control in China. We aimed to combine genomic, spatial, and epidemiological data to describe the dynamics of tuberculosis in an urban setting with large numbers of migrants. METHODS:We did a population-based study of culture-positive Mycobacterium tuberculosis isolates in Songjiang, Shanghai. We used whole-genome sequencing to discriminate apparent genetic clusters of M tuberculosis sharing identical variable-number-tandem-repeat (VNTR) patterns, and analysed the relations between proximity of residence and the risk of genomically clustered M tuberculosis. Finally, we used genomic, spatial, and epidemiological data to estimate time of infection and transmission links among migrants and residents. FINDINGS:Between Jan 1, 2009, and Dec 31, 2015, 1620 cases of culture-positive tuberculosis were recorded, 1211 (75%) of which occurred among internal migrants. 150 (69%) of 218 people sharing identical VNTR patterns had isolates within ten single-nucleotide polymorphisms (SNPs) of at least one other strain, consistent with recent transmission of M tuberculosis. Pairs of strains collected from individuals living in close proximity were more likely to be genetically similar than those from individuals who lived far away-for every additional km of distance between patients' homes, the odds that genotypically matched strains were within ten SNPs of each other decreased by about 10% (OR 0·89 [95% CI 0·87-0·91]; p<0·0001). We inferred that transmission from residents to migrants occurs as commonly as transmission from migrants to residents, and we estimated that more than two-thirds of migrants in genomic clusters were infected locally after migration. INTERPRETATION:The primary mechanism driving local incidence of tuberculosis in urban centres is local transmission between both migrants and residents. Combined analysis of epidemiological, genomic, and spatial data contributes to a richer understanding of local transmission dynamics and should inform the design of more effective interventions. FUNDING:National Natural Science Foundation of China, National Science and Technology Major Project of China, and US National Institutes of Health.
| S-EPMC6035060 | biostudies-literature
Project description:BACKGROUND:This paper is about spatial patterns of by corona virus disease-2019 (COVID-19). METHODS:Using data for the first 21 weeks from municipalities in Catalonia, we analyse whether reported positive cases appear randomly or following some kind of spatial dependence. Global and local measures of spatial autocorrelation are used. RESULTS:There are some clusters alongside Catalan municipalities that change over time. CONCLUSIONS:Use of spatial analysis techniques is suggested to identify spatial disease patterns and to provide spatially disaggregated public health policy recommendations.
| S-EPMC7454828 | biostudies-literature
Project description:This paper examines sectoral productivity shocks of the COVID-19 pandemic, their aggregate impact, and the possible compensatory effects of improving productivity in infrastructure-related sectors. We employ the KLEMS annual dataset for a group of OECD and Latin America and the Caribbean countries, complemented with high-frequency data for 2020. First, we estimate a panel vector autoregression of growth rates in sector level labor productivity to specify the nature and size of sectoral shocks using the historical data. We then run impulse-response simulations of one standard deviation shocks in the sectors that were most affected by COVID-19. We estimate that the pandemic cut economy-wide labor productivity by 4.9% in Latin America, and by 3.5% for the entire sample. Finally, by modeling the long-run relationship between productivity shocks in the sectors most affected by COVID-19, we find that large productivity improvements in infrastructure-equivalent to at least three times the historical rates of productivity gains-may be needed to fully compensate for the negative productivity losses traceable to COVID-19.Supplementary informationThe online version contains supplementary material available at 10.1007/s41885-021-00098-z.
| S-EPMC8777183 | biostudies-literature