scholarly journals Incorporating Human Movement Data to Improve Epidemiological Estimates for 2019-nCoV

2020 ◽  
Author(s):  
Zhidong Cao ◽  
Qingpeng Zhang ◽  
Xin Lu ◽  
Dirk Pfeiffer ◽  
Lei Wang ◽  
...  
Keyword(s):  
Latent Infection ◽  
Human Mobility ◽  
Mainland China ◽  
Human Movement ◽  
Hubei Province ◽  
The Novel ◽  
Movement Data ◽  
Control And Prevention ◽  
Novel Coronavirus ◽  
Reporting Data

AbstractEstimating the key epidemiological features of the novel coronavirus (2019-nCoV) epidemic proves to be challenging, given incompleteness and delays in early data reporting, in particular, the severe under-reporting bias in the epicenter, Wuhan, Hubei Province, China. As a result, the current literature reports widely varying estimates. We developed an alternative geo-stratified debiasing estimation framework by incorporating human mobility with case reporting data in three stratified zones, i.e., Wuhan, Hubei Province excluding Wuhan, and mainland China excluding Hubei. We estimated the latent infection ratio to be around 0.12% (18,556 people) and the basic reproduction number to be 3.24 in Wuhan before the city’s lockdown on January 23, 2020. The findings based on this debiasing framework have important implications to prioritization of control and prevention efforts.One Sentence SummaryA geo-stratified debiasing approach incorporating human movement data was developed to improve modeling of the 2019-nCoV epidemic.

scholarly journals Monitoring the COVID-19 epidemic with nationwide telecommunication data

2021 ◽  
Vol 118 (26) ◽  
pp. e2100664118
Author(s):  
Joel Persson ◽  
Jurriaan F. Parie ◽  
Stefan Feuerriegel
Keyword(s):  
Large Scale ◽  
Human Mobility ◽  
Human Movement ◽  
Spatiotemporal Analysis ◽  
Decision Makers ◽  
The Novel ◽  
School Closures ◽  
Time Period ◽  
Policy Measures ◽  
Novel Coronavirus

In response to the novel coronavirus disease (COVID-19), governments have introduced severe policy measures with substantial effects on human behavior. Here, we perform a large-scale, spatiotemporal analysis of human mobility during the COVID-19 epidemic. We derive human mobility from anonymized, aggregated telecommunication data in a nationwide setting (Switzerland; 10 February to 26 April 2020), consisting of ∼1.5 billion trips. In comparison to the same time period from 2019, human movement in Switzerland dropped by 49.1%. The strongest reduction is linked to bans on gatherings of more than five people, which are estimated to have decreased mobility by 24.9%, followed by venue closures (stores, restaurants, and bars) and school closures. As such, human mobility at a given day predicts reported cases 7 to 13 d ahead. A 1% reduction in human mobility predicts a 0.88 to 1.11% reduction in daily reported COVID-19 cases. When managing epidemics, monitoring human mobility via telecommunication data can support public decision makers in two ways. First, it helps in assessing policy impact; second, it provides a scalable tool for near real-time epidemic surveillance, thereby enabling evidence-based policies.

scholarly journals Human Mobility Restrictions and the Spread of the Novel Coronavirus (2019-nCoV) in China

2020 ◽  
Author(s):  
Hanming Fang ◽  
Long Wang ◽  
Yang Yang
Keyword(s):  
Human Mobility ◽  
Hubei Province ◽  
The Novel ◽  
Chinese Cities ◽  
Social Distancing ◽  
Spring Festival ◽  
The Social ◽  
Novel Coronavirus ◽  
The Impact ◽  
The City

AbstractWe quantify the causal impact of human mobility restrictions, particularly the lockdown of the city of Wuhan on January 23, 2020, on the containment and delay of the spread of the Novel Coronavirus (2019-nCoV). We employ a set of difference-in-differences (DID) estimations to disentangle the lockdown effect on human mobility reductions from other confounding effects including panic effect, virus effect, and the Spring Festival effect. We find that the lockdown of Wuhan reduced inflow into Wuhan by 76.64%, outflows from Wuhan by 56.35%, and within-Wuhan movements by 54.15%. We also estimate the dynamic effects of up to 22 lagged population inflows from Wuhan and other Hubei cities, the epicenter of the 2019-nCoV outbreak, on the destination cities’ new infection cases. We find, using simulations with these estimates, that the lockdown of the city of Wuhan on January 23, 2020 contributed significantly to reducing the total infection cases outside of Wuhan, even with the social distancing measures later imposed by other cities. We find that the COVID-19 cases would be 64.81% higher in the 347 Chinese cities outside Hubei province, and 52.64% higher in the 16 non-Wuhan cities inside Hubei, in the counterfactual world in which the city of Wuhan were not locked down from January 23, 2020. We also find that there were substantial undocumented infection cases in the early days of the 2019-nCoV outbreak in Wuhan and other cities of Hubei province, but over time, the gap between the officially reported cases and our estimated “actual” cases narrows significantly. We also find evidence that enhanced social distancing policies in the 63 Chinese cities outside Hubei province are effective in reducing the impact of population inflows from the epi-center cities in Hubei province on the spread of 2019-nCoV virus in the destination cities elsewhere.JEL CodesI18, I10.

scholarly journals Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Meng-Chun Chang ◽  
Rebecca Kahn ◽  
Yu-An Li ◽  
Cheng-Sheng Lee ◽  
Caroline O. Buckee ◽  
...  
Keyword(s):  
Disease Surveillance ◽  
Initial Conditions ◽  
Human Mobility ◽  
Human Movement ◽  
Disease Spread ◽  
Spatial Spread ◽  
Movement Data ◽  
Intercity Travel ◽  
Travel Restrictions ◽  
The Impact

Abstract Background As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. Methods In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. Results We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. Conclusions To prepare for the potential spread within Taiwan, we utilized Facebook’s aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions.

scholarly journals Evolving epidemiology of novel coronavirus diseases 2019 and possible interruption of local transmission outside Hubei Province in China: a descriptive and modeling study

2020 ◽  
Author(s):  
Juanjuan Zhang ◽  
Maria Litvinova ◽  
Wei Wang ◽  
Yan Wang ◽  
Xiaowei Deng ◽  
...  
Keyword(s):  
Age Groups ◽  
Mainland China ◽  
The Elderly ◽  
Hubei Province ◽  
Epidemic Threshold ◽  
Epidemic Dynamics ◽  
Serial Interval ◽  
The Mean ◽  
Novel Coronavirus ◽  
Local Transmission

AbstractBackgroundThe COVID-19 epidemic originated in Wuhan City of Hubei Province in December 2019 and has spread throughout China. Understanding the fast evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy.MethodsWe collected individual information on 8,579 laboratory-confirmed cases from official publically sources reported outside Hubei in mainland China, as of February 17, 2020. We estimated the temporal variation of the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level.ResultsThe median age of the cases was 44 years, with an increasing of cases in younger age groups and the elderly as the epidemic progressed. The delay from symptom onset to hospital admission decreased from 4.4 days (95%CI: 0.0-14.0) until January 27 to 2.6 days (0.0-9.0) from January 28 to February 17. The mean incubation period was estimated at 5.2 days (1.8-12.4) and the mean serial interval at 5.1 days (1.3-11.6). The epidemic dynamics in provinces outside Hubei was highly variable, but consistently included a mix of case importations and local transmission. We estimate that the epidemic was self-sustained for less than three weeks with Rt reaching peaks between 1.40 (1.04-1.85) in Shenzhen City of Guangdong Province and 2.17 (1.69-2.76) in Shandong Province. In all the analyzed locations (n=10) Rt was estimated to be below the epidemic threshold since the end of January.ConclusionOur findings suggest that the strict containment measures and movement restrictions in place may contribute to the interruption of local COVID-19 transmission outside Hubei Province. The shorter serial interval estimated here implies that transmissibility is not as high as initial estimates suggested.

scholarly journals Brief Report of Guidelines and Protocols for the Management of COVID-19

2020 ◽  
Vol 3 (2) ◽  
pp. 124-133
Author(s):  
Fabricia Oliveira Oliveira ◽  
Larissa Moraes dos Santos Fonseca ◽  
Roberto Badaró ◽  
Bruna Aparecida Souza Machado
Keyword(s):  
Management Strategies ◽  
Virus Transmission ◽  
The Novel ◽  
Data Flows ◽  
The World ◽  
Control And Prevention ◽  
Novel Coronavirus ◽  
Guidelines And Recommendations ◽  
The Impact ◽  
Coordinate Data

In less than a year, the novel coronavirus rapidly changed the world scenario. To dealing with the fast spread of the disease, health associations coordinate data flows and issue guidelines to better mitigate the impact of the threat. Also, scientific groups around the world are working to ensure that all information about the mechanisms of the virus, transmission, and disease clinics is updated as the disease progresses. The objective of this study was to present the guidelines and recommendations for preventing, management strategies, clarifications about pandemics disinformation, and diagnosing COVID-19 infection in human specimens adopted from the main health centers and institutions in the world, such as WHO and Centers for Disease Control and Prevention (CDC). It is important to highlight that the rapid and effective enforcement of existing international and national action plans, as well as parallel review and improvisation, is facilitating the affected countries to contain transmission and possibly delay the peak of outbreak and mortality.

scholarly journals COMPARATIVE ANALYSIS OF COVID-19 EPIDEMIC IN HUBEI PROVINCE AND REST PARTS OF MAINLAND CHINA

2020 ◽  
pp. 1-3
Author(s):  
Youfu Ke ◽  
Zemin Chen ◽  
Bo Peng ◽  
Hoyan Wong ◽  
Yunkeung Wong ◽  
...  
Keyword(s):  
Growth Rates ◽  
Mainland China ◽  
Diagnosis And Treatment ◽  
The Novel ◽  
Fatality Rate ◽  
Treatment Standards ◽  
Daily Observation ◽  
Novel Coronavirus ◽  
Pneumonia Diagnosis ◽  
Close Contacts

Background: China 's national-level anti-COVID-19 campaign has been going on for a month. With the development of the epidemic, it is found that COVID-19 severity in Hubei province (Hubei) is different from the rest of mainland China (Rest of China). It is necessary to compare the two areas, summarize experiences and lessons, analyze the epidemic trend and further point out the direction for the campaign. Methods: Prevent, quarantine and treat the disease according to The Novel Coronavirus Infected Pneumonia Diagnosis and Treatment Standards. Collect the numbers of total close contacts, daily observation cases, daily suspected cases, total conrmed cases, daily severe cases, total deaths from January 20 to February 19, input them into SPSS 25 and Microsoft ofce 2019 excel for data processing, statistical analysis and drawing. Findings: Total conrmed cases in Hubei account for 83.2% of the country. Daily suspected cases growth rates for both areas have become negative since February 9. Daily observation cases in Rest of China reached highest point on February 5 as opposed to February 13 in Hubei, and total close contacts growth rates for the last three days are declining steadily to 1.9% and 3.8% respectively. Total conrmed cases growth rate has hit the lowest levels in Rest of China at 0.34% by comparison with 0.57% in Hubei. Mean fatality rate and mean percentage of severe cases for the last three days in Rest of China are 0.67% and 5.83% in contrast to 3.12% and 18.2% in Hubei. There have been very signicant differences in fatality rate and percentage of severe cases existing in the two areas since January 23 and 24 respectively (P<0.01). Interpretation: Hubei is the main epidemic area. COVID-19 has low fatality rate and high transmissibility. Cutting off the source of infection is pivotal in containing COVID-19 outbreak and has a guiding effect on prevention and control of pandemic worldwide. The Novel Coronavirus Infected Pneumonia Diagnosis and Treatment Standards has played an important role in helping medical staff across the country to ght the epidemic. Coordinating national medical resources to support disaster areas, making full use of the existing facilities to isolate and quarantine, providing timely and accurate treatment can reduce fatality rate. Further efforts are needed to develop highly effective Chinese medicines, western drugs and vaccines in order to eradicate the virus or prevent the epidemic from continuing.

scholarly journals THE INFLUENCE OF CHRONIC DISEASES ON THE MANIFESTATION OF COVID-19 INFECTION

2021 ◽  
pp. 126-132
Author(s):  
S. O. Yastremska ◽  
O. M. Krekhovska-Lepiavko ◽  
B. A. Lokay ◽  
O. V. Bushtynska ◽  
S. V. Danchak
Keyword(s):  
Chronic Diseases ◽  
Case Fatality ◽  
The Novel ◽  
Fatality Rate ◽  
The World ◽  
Control And Prevention ◽  
The Usa ◽  
Life Threatening ◽  
One Year ◽  
Novel Coronavirus

Summary. The first known case of infection from the novel coronavirus was recorded almost one year ago, in China’s Hubei province. The city of Wuhan was infamous the world over as the original virus epicenter, seeing more than half of China’s reported cases and deaths. The outbreak of COVID-19 virus, as sickened more than 14.7 million people. At least 610.200 people have died. The aim of the study – to analyze and systematize the literature data about the influence of chronic diseases on the manifestation of COVID-19 infection. Materials and Methods. The study uses publications of the world scientific literature on COVID-19 infection, in particular the causes and mechanisms of its development, treatment, complications and its consequences as well as the influence of different chronic disorders on the course of COVID-19. Results. A sample of patients hospitalized with COVID-19 across 14 states of the USA in March was analyzed by The Centers for Disease Control and Prevention. It was found that many (89 %) had underlying health problem and 94 % of patients were at the age 65 and older. The case fatality rate for those under age 60 was 1.4 percent. For those over age 60, the fatality rate jumps to 4.5 percent. The older the population, the higher the fatality rate. For those 80 and over, Covid-19 appears to have a 13.4 percent fatality rate. Moreover, it was recognized, that older adults don't present in a typical way of the course of different disorders, and we're seeing that with Covid-19 as well. Conclusions. Chronic diseases and conditions are on the rise worldwide. COVID-19 became the most challenging pandemic influencing all countries worldwide. Chronic diseases are suggested to be one of the main causes of different life-threatening complications of COVID-19 infection and one of the main factors of poor prognosis for the patients.

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