Project description:Comparable data on spatial accessibility by different travel modes are frequently needed to understand how city regions function. Here, we present a spatial dataset called the Helsinki Region Travel Time Matrix that has been calculated for 2013, 2015 and 2018. This longitudinal dataset contains travel time and distance information between all 250 metres statistical grid cell centroids in the Capital Region of Helsinki, Finland. The dataset is multimodal and multitemporal by nature: all typical transport modes (walking, cycling, public transport, and private car) are included and calculated separately for the morning rush hour and midday for an average working day. We followed a so-called door-to-door principle, making the information between travel modes comparable. The analyses were based primarily on open data sources, and all the tools that were used to produce the data are openly available. The matrices form a time-series that can reveal the accessibility conditions within the city and allow comparisons of the changes in accessibility in the region, which support spatial planning and decision-making.
Project description:The current rampant coronavirus infection in humans, commonly known as COVID-19, a pandemic that may cause mortality in humans, has been declared a global emergency by the World Health Organization (WHO). The morbidity and mortality rates due to the pandemic are increasing rapidly worldwide, with the USA most affected by the disease. The source COVID-19 is not absolutely clear; however, the disease may be transmitted by either by COVID-19-positive individuals or from a contaminated environment. In this review, we focused on how the COVID-19 virus is transmitted in the community. An extensive literature search was conducted using specific keywords and criteria. Based on the published report, it is concluded that COVID-19 is primarily transmitted human-to-human via oral and respiratory aerosols and droplets with the virus-contaminated environment play a lesser role in the propagation of disease. Healthcare providers and the elderly with comorbidities are especially susceptible to the infection.
Project description:On 30 January 2020, WHO declared coronavirus (COVID-19) a global public health emergency. As of 12 March 2020, 125 048 confirmed COVID-19 cases in 118 countries had been reported. On 12 March 2020, the first case in the Pacific islands was reported in French Polynesia; no other Pacific island country or territory has reported cases. The purpose of our analysis is to show how travellers may introduce COVID-19 into the Pacific islands and discuss the role robust health systems play in protecting health and reducing transmission risk. We analyse travel and Global Health Security Index data using a scoring tool to produce quantitative estimates of COVID-19 importation risk, by departing and arriving country. Our analysis indicates that, as of 12 March 2020, the highest risk air routes by which COVID-19 may be imported into the Pacific islands are from east Asian countries (specifically, China, Korea and Japan) to north Pacific airports (likely Guam, Commonwealth of the Northern Mariana Islands or, to a less extent, Palau); or from China, Japan, Singapore, the United States of America or France to south Pacific ports (likely, Fiji, Papua New Guinea, French Polynesia or New Caledonia). Other importation routes include from other east Asian countries to Guam, and from Australia, New Zealand and other European countries to the south Pacific. The tool provides a useful method for assessing COVID-19 importation risk and may be useful in other settings.
Project description:Travel restrictions and physical distancing have been implemented across the world to mitigate the coronavirus disease 2019 (COVID-19) pandemic, but studies are needed to understand their effectiveness across regions and time. Based on the population mobility metrics derived from mobile phone geolocation data across 135 countries or territories during the first wave of the pandemic in 2020, we built a metapopulation epidemiological model to measure the effect of travel and contact restrictions on containing COVID-19 outbreaks across regions. We found that if these interventions had not been deployed, the cumulative number of cases could have shown a 97-fold (interquartile range 79-116) increase, as of May 31, 2020. However, their effectiveness depended upon the timing, duration, and intensity of the interventions, with variations in case severity seen across populations, regions, and seasons. Additionally, before effective vaccines are widely available and herd immunity is achieved, our results emphasize that a certain degree of physical distancing at the relaxation of the intervention stage will likely be needed to avoid rapid resurgences and subsequent lockdowns.
Project description:BackgroundTo contain the spread of COVID-19, a cordon sanitaire was put in place in Wuhan prior to the Lunar New Year, on 23 January 2020. We assess the efficacy of the cordon sanitaire to delay the introduction and onset of local transmission of COVID-19 in other major cities in mainland China.MethodsWe estimated the number of infected travellers from Wuhan to other major cities in mainland China from November 2019 to February 2020 using previously estimated COVID-19 prevalence in Wuhan and publicly available mobility data. We focused on Beijing, Chongqing, Hangzhou, and Shenzhen as four representative major cities to identify the potential independent contribution of the cordon sanitaire and holiday travel. To do this, we simulated outbreaks generated by infected arrivals in these destination cities using stochastic branching processes. We also modelled the effect of the cordon sanitaire in combination with reduced transmissibility scenarios to simulate the effect of local non-pharmaceutical interventions.ResultsWe find that in the four cities, given the potentially high prevalence of COVID-19 in Wuhan between December 2019 and early January 2020, local transmission may have been seeded as early as 1-8 January 2020. By the time the cordon sanitaire was imposed, infections were likely in the thousands. The cordon sanitaire alone did not substantially affect the epidemic progression in these cities, although it may have had some effect in smaller cities. Reduced transmissibility resulted in a notable decrease in the incidence of infection in the four studied cities.ConclusionsOur results indicate that sustained transmission was likely occurring several weeks prior to the implementation of the cordon sanitaire in four major cities of mainland China and that the observed decrease in incidence was likely attributable to other non-pharmaceutical, transmission-reducing interventions.
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.
Project description:BackgroundThe degree to which the 2019 novel coronavirus disease (COVID-19) pandemic will affect the US human immunodeficiency virus (HIV) epidemic is unclear.MethodsWe used the Johns Hopkins Epidemiologic and Economic Model to project HIV infections from 2020 to 2025 in 32 US metropolitan statistical areas (MSAs). We sampled a range of effects of the pandemic on sexual transmission (0-50% reduction), viral suppression among people with HIV (0-40% reduction), HIV testing (0-50% reduction), and pre-exposure prophylaxis use (0-30% reduction), and indexed reductions over time to Google Community Mobility Reports.ResultsSimulations projected reported diagnoses would drop in 2020 and rebound in 2021 or 2022, regardless of underlying incidence. If sexual transmission normalized by July 2021 and HIV care normalized by January 2022, we projected 1161 (1%) more infections from 2020 to 2025 across all 32 cities than if COVID-19 had not occurred. Among "optimistic" simulations in which sexual transmission was sharply reduced and viral suppression was maintained we projected 8% lower incidence (95% credible interval: 14% lower to no change). Among "pessimistic" simulations where sexual transmission was largely unchanged but viral suppression fell, we projected 11% higher incidence (1-21% higher). MSA-specific projections are available at www.jheem.org?covid.ConclusionsThe effects of COVID-19 on HIV transmission remain uncertain and differ between cities. Reported diagnoses of HIV in 2020-2021 are likely to correlate poorly with underlying incidence. Minimizing disruptions to HIV care is critical to mitigating negative effects of the COVID-19 pandemic on HIV transmission.
Project description:Cities across China implemented stringent social distancing measures in early 2020 to curb coronavirus disease outbreaks. We estimated the speed with which these measures contained transmission in cities. A 1-day delay in implementing social distancing resulted in a containment delay of 2.41 (95% CI 0.97-3.86) days.
Project description:This study attempts to assess the relationship between risk perception, risk knowledge, and travel intentions of Chinese leisure travelers during the COVID-19 pandemic in the framework of social contagion and risk communication theories by analyzing a sample of 1,209 travelers through structural equation modeling (SEM) and path analysis. We used the process macro of Hayes to analyze the moderation effects of age, gender, and education between risk perception, media and interpersonal communication, and risk knowledge. It was found that travelers were more concerned about self-efficacy than severity. Risk perception of travelers predicts the information-seeking process of tourists. This process helps travelers to accumulate risk information that influences their travel intentions. Travelers give more importance to interpersonal (contagion) communication in making a traveling decision. Demographic factors influence traveling decision-making; women travelers were found to be more risk resilient than men. Young travelers seek information at low- and old travelers at high-risk levels. Marketing implications also provided.