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1.
JMIR Public Health Surveill ; 7(3): e26719, 2021 03 24.
Article in English | MEDLINE | ID: covidwho-2197901

ABSTRACT

BACKGROUND: Patient travel history can be crucial in evaluating evolving infectious disease events. Such information can be challenging to acquire in electronic health records, as it is often available only in unstructured text. OBJECTIVE: This study aims to assess the feasibility of annotating and automatically extracting travel history mentions from unstructured clinical documents in the Department of Veterans Affairs across disparate health care facilities and among millions of patients. Information about travel exposure augments existing surveillance applications for increased preparedness in responding quickly to public health threats. METHODS: Clinical documents related to arboviral disease were annotated following selection using a semiautomated bootstrapping process. Using annotated instances as training data, models were developed to extract from unstructured clinical text any mention of affirmed travel locations outside of the continental United States. Automated text processing models were evaluated, involving machine learning and neural language models for extraction accuracy. RESULTS: Among 4584 annotated instances, 2659 (58%) contained an affirmed mention of travel history, while 347 (7.6%) were negated. Interannotator agreement resulted in a document-level Cohen kappa of 0.776. Automated text processing accuracy (F1 85.6, 95% CI 82.5-87.9) and computational burden were acceptable such that the system can provide a rapid screen for public health events. CONCLUSIONS: Automated extraction of patient travel history from clinical documents is feasible for enhanced passive surveillance public health systems. Without such a system, it would usually be necessary to manually review charts to identify recent travel or lack of travel, use an electronic health record that enforces travel history documentation, or ignore this potential source of information altogether. The development of this tool was initially motivated by emergent arboviral diseases. More recently, this system was used in the early phases of response to COVID-19 in the United States, although its utility was limited to a relatively brief window due to the rapid domestic spread of the virus. Such systems may aid future efforts to prevent and contain the spread of infectious diseases.


Subject(s)
Communicable Diseases, Emerging/diagnosis , Electronic Health Records , Information Storage and Retrieval/methods , Public Health Surveillance/methods , Travel/statistics & numerical data , Algorithms , COVID-19/epidemiology , Communicable Diseases, Emerging/epidemiology , Feasibility Studies , Female , Humans , Machine Learning , Male , Middle Aged , Natural Language Processing , Reproducibility of Results , United States/epidemiology
2.
3.
Elife ; 92020 08 13.
Article in English | MEDLINE | ID: covidwho-2155738

ABSTRACT

As of 1 May 2020, there had been 6808 confirmed cases of COVID-19 in Australia. Of these, 98 had died from the disease. The epidemic had been in decline since mid-March, with 308 cases confirmed nationally since 14 April. This suggests that the collective actions of the Australian public and government authorities in response to COVID-19 were sufficiently early and assiduous to avert a public health crisis - for now. Analysing factors that contribute to individual country experiences of COVID-19, such as the intensity and timing of public health interventions, will assist in the next stage of response planning globally. We describe how the epidemic and public health response unfolded in Australia up to 13 April. We estimate that the effective reproduction number was likely below one in each Australian state since mid-March and forecast that clinical demand would remain below capacity thresholds over the forecast period (from mid-to-late April).


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Pandemics , Pneumonia, Viral/epidemiology , Adolescent , Adult , Age Distribution , Aged , Aged, 80 and over , Australia/epidemiology , COVID-19 , Child , Child, Preschool , Communicable Disease Control/methods , Communicable Disease Control/organization & administration , Communicable Disease Control/statistics & numerical data , Coronavirus Infections/prevention & control , Female , Forecasting , Geography, Medical , Hospitalization/statistics & numerical data , Humans , Infant , Infant, Newborn , Male , Middle Aged , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Public Health , Quarantine , SARS-CoV-2 , Travel , Young Adult
4.
Euro Surveill ; 27(43)2022 10.
Article in English | MEDLINE | ID: covidwho-2154580

ABSTRACT

BackgroundTracking person-to-person SARS-CoV-2 transmission in the population is important to understand the epidemiology of community transmission and may contribute to the containment of SARS-CoV-2. Neither contact tracing nor genomic surveillance alone, however, are typically sufficient to achieve this objective.AimWe demonstrate the successful application of the integrated genomic surveillance (IGS) system of the German city of Düsseldorf for tracing SARS-CoV-2 transmission chains in the population as well as detecting and investigating travel-associated SARS-CoV-2 infection clusters.MethodsGenomic surveillance, phylogenetic analysis, and structured case interviews were integrated to elucidate two genetically defined clusters of SARS-CoV-2 isolates detected by IGS in Düsseldorf in July 2021.ResultsCluster 1 (n = 67 Düsseldorf cases) and Cluster 2 (n = 36) were detected in a surveillance dataset of 518 high-quality SARS-CoV-2 genomes from Düsseldorf (53% of total cases, sampled mid-June to July 2021). Cluster 1 could be traced back to a complex pattern of transmission in nightlife venues following a putative importation by a SARS-CoV-2-infected return traveller (IP) in late June; 28 SARS-CoV-2 cases could be epidemiologically directly linked to IP. Supported by viral genome data from Spain, Cluster 2 was shown to represent multiple independent introduction events of a viral strain circulating in Catalonia and other European countries, followed by diffuse community transmission in Düsseldorf.ConclusionIGS enabled high-resolution tracing of SARS-CoV-2 transmission in an internationally connected city during community transmission and provided infection chain-level evidence of the downstream propagation of travel-imported SARS-CoV-2 cases.


Subject(s)
COVID-19 , Communicable Diseases, Imported , Humans , SARS-CoV-2/genetics , Travel , Communicable Diseases, Imported/epidemiology , COVID-19/epidemiology , Phylogeny , Contact Tracing , Germany/epidemiology , Genomics
5.
JMIR Public Health Surveill ; 7(8): e29957, 2021 Aug 30.
Article in English | MEDLINE | ID: covidwho-2141339

ABSTRACT

BACKGROUND: Association between human mobility and disease transmission has been established for COVID-19, but quantifying the levels of mobility over large geographical areas is difficult. Google has released Community Mobility Reports (CMRs) containing data about the movement of people, collated from mobile devices. OBJECTIVE: The aim of this study is to explore the use of CMRs to assess the role of mobility in spreading COVID-19 infection in India. METHODS: In this ecological study, we analyzed CMRs to determine human mobility between March and October 2020. The data were compared for the phases before the lockdown (between March 14 and 25, 2020), during lockdown (March 25-June 7, 2020), and after the lockdown (June 8-October 15, 2020) with the reference periods (ie, January 3-February 6, 2020). Another data set depicting the burden of COVID-19 as per various disease severity indicators was derived from a crowdsourced API. The relationship between the two data sets was investigated using the Kendall tau correlation to depict the correlation between mobility and disease severity. RESULTS: At the national level, mobility decreased from -38% to -77% for all areas but residential (which showed an increase of 24.6%) during the lockdown compared to the reference period. At the beginning of the unlock phase, the state of Sikkim (minimum cases: 7) with a -60% reduction in mobility depicted more mobility compared to -82% in Maharashtra (maximum cases: 1.59 million). Residential mobility was negatively correlated (-0.05 to -0.91) with all other measures of mobility. The magnitude of the correlations for intramobility indicators was comparatively low for the lockdown phase (correlation ≥0.5 for 12 indicators) compared to the other phases (correlation ≥0.5 for 45 and 18 indicators in the prelockdown and unlock phases, respectively). A high correlation coefficient between epidemiological and mobility indicators was observed for the lockdown and unlock phases compared to the prelockdown phase. CONCLUSIONS: Mobile-based open-source mobility data can be used to assess the effectiveness of social distancing in mitigating disease spread. CMR data depicted an association between mobility and disease severity, and we suggest using this technique to supplement future COVID-19 surveillance.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Cell Phone , Geographic Information Systems , Pandemics , Travel/statistics & numerical data , Humans , India/epidemiology
6.
Am J Prev Med ; 63(6): 1053-1061, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2129802

ABSTRACT

INTRODUCTION: As the first step in the HIV care continuum, timely diagnosis is central to reducing transmission of the virus and ending the HIV epidemic. Studies have shown that distance from a testing site is essential for ease of access to services and educational material. This study shows how location-allocation analysis can be used to improve allocation of HIV testing services utilizing existing publicly available data from 2015 to 2019 on HIV prevalence, testing site location, and factors related to HIV in Philadelphia, Pennsylvania. METHODS: The ArcGIS Location-Allocation analytic tool was used to calculate locations for HIV testing sites using a method that minimizes the distance between demand-point locations and service facilities. ZIP code level demand was initially specified on the basis of the percentage of late HIV diagnoses and in a sensitivity analysis on the basis of a composite of multiple factors. Travel time and distance from demand to facilities determined the facility location allocation. This analysis was conducted from 2021 to 2022. RESULTS: Compared with the 37 facilities located in 20 (43%) Philadelphia ZIP codes, the model proposed reallocating testing facilities to 37 (79%) ZIP codes using percent late diagnoses to define demand. On average, this would reduce distance to the facilities by 65% and travel time to the facilities by 56%. Results using the sensitivity analysis were similar. CONCLUSIONS: A wider distribution of HIV testing services across the city of Philadelphia may reduce distance and travel time to facilities, improve accessibility of testing, and in turn increase the percentage of people with knowledge of their status.


Subject(s)
Continuity of Patient Care , HIV Infections , Humans , Philadelphia/epidemiology , Knowledge , Travel , HIV Infections/diagnosis , HIV Infections/epidemiology , HIV Infections/prevention & control
7.
Dtsch Med Wochenschr ; 147(12): 729-730, 2022 06.
Article in German | MEDLINE | ID: covidwho-2133720

Subject(s)
Travel Medicine , Travel , Humans
8.
Front Public Health ; 10: 907005, 2022.
Article in English | MEDLINE | ID: covidwho-2120996

ABSTRACT

This study explored the willingness and purchase of travel insurance during the COVID-19 pandemic amongst working adults to ensure their safety and welfare through the lens of the theory of planned behavior. Primary data were gathered from 1,118 working adults across Malaysia and analyzed using the partial least squares structural equation modeling. The study outcomes revealed that attitude toward travel insurance was significantly influenced by insurance literacy, perceived health risk, and health consciousness. The willingness of working adults to purchase travel insurance was highly influenced by attitudes, subjective norms, and perceived behavioral controls but unaffected by perceived product risks. The purchase of travel insurance was positively influenced by the willingness to purchase travel insurance. In fact, travel insurance literacy and perceived health risk should be emphasized amongst working adults to encourage them to purchase travel insurance policies for traveling abroad.


Subject(s)
COVID-19 , Insurance , Adult , Consumer Behavior , Humans , Pandemics , Travel
9.
Sci Rep ; 12(1): 19492, 2022 Nov 14.
Article in English | MEDLINE | ID: covidwho-2119364

ABSTRACT

Pre-vaccine SARS-CoV-2 seroprevalence data from Germany are scarce outside hotspots, and socioeconomic disparities remained largely unexplored. The nationwide representative RKI-SOEP study (15,122 participants, 18-99 years, 54% women) investigated seroprevalence and testing in a supplementary wave of the Socio-Economic-Panel conducted predominantly in October-November 2020. Self-collected oral-nasal swabs were PCR-positive in 0.4% and Euroimmun anti-SARS-CoV-2-S1-IgG ELISA from dry-capillary-blood antibody-positive in 1.3% (95% CI 0.9-1.7%, population-weighted, corrected for sensitivity = 0.811, specificity = 0.997). Seroprevalence was 1.7% (95% CI 1.2-2.3%) when additionally correcting for antibody decay. Overall infection prevalence including self-reports was 2.1%. We estimate 45% (95% CI 21-60%) undetected cases and lower detection in socioeconomically deprived districts. Prior SARS-CoV-2 testing was reported by 18% from the lower educational group vs. 25% and 26% from the medium and high educational group (p < 0.001, global test over three categories). Symptom-triggered test frequency was similar across educational groups. Routine testing was more common in low-educated adults, whereas travel-related testing and testing after contact with infected persons was more common in highly educated groups. This countrywide very low pre-vaccine seroprevalence in Germany at the end of 2020 can serve to evaluate the containment strategy. Our findings on social disparities indicate improvement potential in pandemic planning for people in socially disadvantaged circumstances.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Adult , Female , Male , Seroepidemiologic Studies , COVID-19 Testing , Travel , COVID-19/diagnosis , COVID-19/epidemiology , Travel-Related Illness , Antibodies, Viral , Immunoglobulin G
10.
Sci Rep ; 12(1): 19780, 2022 Nov 17.
Article in English | MEDLINE | ID: covidwho-2119290

ABSTRACT

Human behavioural changes are poorly understood, and this limitation has been a serious obstacle to epidemic forecasting. It is generally understood that people change their respective behaviours to reduce the risk of infection in response to the status of an epidemic or government interventions. We must first identify the factors that lead to such decision-making to predict these changes. However, due to an absence of a method to observe decision-making for future behaviour, understanding the behavioural responses to disease is limited. Here, we show that accommodation reservation data could reveal the decision-making process that underpins behavioural changes, travel avoidance, for reducing the risk of COVID-19 infections. We found that the motivation to avoid travel with respect to only short-term future behaviours dynamically varied and was associated with the outbreak status and/or the interventions of the government. Our developed method can quantitatively measure and predict a large-scale population's behaviour to determine the future risk of COVID-19 infections. These findings enable us to better understand behavioural changes in response to disease spread, and thus, contribute to the development of reliable long-term forecasting of disease spread.


Subject(s)
COVID-19 , Epidemics , Humans , COVID-19/epidemiology , Travel , Disease Outbreaks/prevention & control , Forecasting
11.
Acta Biotheor ; 71(1): 2, 2022 Nov 17.
Article in English | MEDLINE | ID: covidwho-2116399

ABSTRACT

A modified version of the SEIR model with the effects of vaccination and inter-state movement is proposed to simulate the spread of COVID-19 in Malaysia. A mathematical analysis of the proposed model was performed to derive the basic reproduction number. To enhance the model's forecasting capabilities, the model parameters were estimated using the Nelder-Mead simplex method by fitting the model outputs to the observed data. Our results showed a good fit between the model outputs and available data, where the model was then able to perform short-term predictions. In line with the rapid vaccination program, our model predicted that the COVID-19 cases in the country would decrease by the end of August. Furthermore, our findings indicated that relaxing travel restrictions from a highly vaccinated region to a low vaccinated region would result in an epidemic outbreak.


Subject(s)
COVID-19 , Epidemics , Animals , COVID-19/epidemiology , COVID-19/prevention & control , Malaysia/epidemiology , Travel , Vaccination/methods
12.
Aust J Gen Pract ; 51(11): 879-883, 2022 11.
Article in English | MEDLINE | ID: covidwho-2100931

ABSTRACT

BACKGROUND: International travel is resuming, but the COVID-19 pandemic has radically changed the context in terms of regulation, risks and models of travel. OBJECTIVE: Providing travel health advice is an important role for general practice. The aim of this article is to cover the changed context and wide-ranging implications of the COVID­19 pandemic for travel health advice. DISCUSSION: Travel in the COVID-19 era requires travellers to be well informed and prepared to comply with complex and evolving public health measures. There are changing patterns of infectious disease risk related to the impacts of the pandemic, increasing antimicrobial resistance and climate change. New models of travel include a shift towards greater environmental sustainability.


Subject(s)
COVID-19 , Pandemics , Humans , Pandemics/prevention & control , COVID-19/epidemiology , COVID-19/prevention & control , Travel , Family Practice , Data Collection
13.
Int J Environ Res Public Health ; 19(21)2022 Nov 03.
Article in English | MEDLINE | ID: covidwho-2099530

ABSTRACT

Uncontrolled, large-scale human mobility can amplify a localized disease into a pandemic. Tracking changes in human travel behavior, exploring the relationship between epidemic events and intercity travel generation and attraction under policies will contribute to epidemic prevention efforts, as well as deepen understanding of the essential changes of intercity interactions in the post-epidemic era. To explore the dynamic impact of small-scale localized epidemic events and related policies on intercity travel, a spatial lag model and improved gravity models are developed by using intercity travel data. Taking the localized COVID-19 epidemic in Xi'an, China as an example, the study constructs the travel interaction characterization before or after the pandemic as well as under constraints of regular epidemic prevention policies, whereby significant impacts of epidemic events are explored. Moreover, indexes of the quantified policies are refined to the city level in China to analyze their effects on travel volumes. We highlight the non-negligible impacts of city events and related policies on intercity interaction, which can serve as a reference for travel management in case of such severe events.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Pandemics/prevention & control , Travel , Cities/epidemiology , China/epidemiology
14.
BMC Infect Dis ; 22(1): 808, 2022 Oct 31.
Article in English | MEDLINE | ID: covidwho-2098321

ABSTRACT

BACKGROUND: In 2020, the Japanese government implemented first of two Go To Travel campaigns to promote the tourism sector as well as eating and drinking establishments, especially in remote areas. The present study aimed to explore the relationship between enhanced travel and geographic propagation of COVID-19 across Japan, focusing on the second campaign with nationwide large-scale economic boost in 2020. METHODS: We carried out an interrupted time-series analysis to identify the possible cause-outcome relationship between the Go To Travel campaign and the spread of infection to nonurban areas in Japan. Specifically, we counted the number of prefectures that experienced a weekly incidence of three, five, and seven COVID-19 cases or more per 100,000 population, and we compared the rate of change before and after the campaign. RESULTS: Three threshold values and three different models identified an increasing number of prefectures above the threshold, indicating that the inter-prefectural spread intensified following the launch of the second Go To Travel campaign from October 1st, 2020. The simplest model that accounted for an increase in the rate of change only provided the best fit. We estimated that 0.24 (95% confidence interval 0.15 to 0.34) additional prefectures newly exceeded five COVID-19 cases per 100,000 population per week during the second campaign. CONCLUSIONS: The enhanced movement resulting from the Go To Travel campaign facilitated spatial spread of COVID-19 from urban to nonurban locations, where health-care capacity may have been limited.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Japan/epidemiology , Travel , Hospital Bed Capacity , Incidence
15.
J Environ Public Health ; 2022: 6274670, 2022.
Article in English | MEDLINE | ID: covidwho-2098049

ABSTRACT

The development of the COVID-19 pandemic has had a devastating impact on one Chinese city that has depended heavily on tourism, which is the core focus of the current study. This article uses phenomenological research methods in qualitative research to conduct semistructured and in-depth interviews with travel agency managers in China Highlights. Through the application of tourism resilience theory in the tourism crisis management domain, this article investigates the performance of China Highlights, a local tourism enterprise in Guilin, China, to restore the functioning and growth of the tourism industry in the postpandemic period. The results show that China's tourism industry is in the early stages of the fast growth stage of economic recovery, and tourism enterprises are faced with a significant challenge in determining how to make sound business choices during the pandemic and after the crisis has passed. It proposes that the tourism resilient theory can serve as a modern crisis management model to facilitate tourism enterprises to revive their performance in times of hardship.


Subject(s)
COVID-19 , Humans , COVID-19/prevention & control , Pandemics , Travel , Industry , China
16.
Environ Geochem Health ; 44(9): 3115-3132, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-2094675

ABSTRACT

With the expansion of the global novel coronavirus disease (COVID-19) pandemic, unprecedented interventions have been widely implemented in many countries, including China. In view of this scenario, this research aims to explore the effectiveness of population mobility restriction in alleviating epidemic transmission during different stages of the outbreak. Taking Shenzhen, a city with a large immigrant population in China, as a case study, the real-time reproduction number of COVID-19 is estimated by statistical methods to represent the dynamic spatiotemporal transmission pattern of COVID-19. Furthermore, migration data between Shenzhen and other provinces are collected to investigate the impact of nationwide population flow on near-real-time dynamic reproductive numbers. The results show that traffic flow control between populated cities has an inhibitory effect on urban transmission, but this effect is not significant in the late stage of the epidemic spread in China. This finding implies that the government should limit international and domestic population movement starting from the very early stage of the outbreak. This work confirms the effectiveness of travel restriction measures in the face of COVID-19 in China and provides new insight for densely populated cities in imposing intervention measures at various stages of the transmission cycle.


Subject(s)
COVID-19 , COVID-19/epidemiology , China/epidemiology , Humans , Pandemics/prevention & control , SARS-CoV-2 , Travel
17.
J Epidemiol ; 32(11): 510-518, 2022 Nov 05.
Article in English | MEDLINE | ID: covidwho-2079950

ABSTRACT

BACKGROUND: Increases in human mobility have been linked to rises in novel coronavirus disease 2019 (COVID-19) transmission. The pandemic era in Japan has been characterized by changes in inter-prefectural mobility across state of emergency (SOE) declarations and travel campaigns, but they have yet to be characterized. METHODS: Using Yahoo Japan mobility data extracted from the smartphones of more than 10 million Japanese residents, we calculated the monthly number of inter-prefectural travel instances, stratified by residential prefecture and destination prefecture. We then used this adjacency matrix to calculate two network connectedness metrics, closeness centrality and effective distance, that reliably predict disease transmission. RESULTS: Inter-prefectural mobility and network connectedness decreased most considerably during the first SOE, but this decrease dampened with each successive SOE. Mobility and network connectedness increased during the Go To Travel campaign. Travel volume between distant prefectures decreased more than travel between prefectures with geographic proximity. Closeness centrality was found to be negatively correlated with the rate of COVID-19 infection across prefectures, with the strength of this association increasing in tandem with the infection rate. Changes in effective distance were more visible among geographically isolated prefectures (Hokkaido and Okinawa) than among metropolitan, central prefectures (Tokyo, Aichi, Osaka, and Fukuoka). CONCLUSION: The magnitude of reductions in human mobility decreased with each subsequent state of emergency, consistent with pandemic fatigue. The association between network connectedness and rates of COVID-19 infection remained visible throughout the entirety of the pandemic period, suggesting that inter-prefectural mobility may have contributed to disease spread.


Subject(s)
COVID-19 , Pandemics , Humans , COVID-19/epidemiology , Japan/epidemiology , Travel , Tokyo
18.
PLoS One ; 17(10): e0276276, 2022.
Article in English | MEDLINE | ID: covidwho-2079764

ABSTRACT

COVID-19, as the most significant epidemic of the century, infected 467 million people and took the lives of more than 6 million individuals as of March 19, 2022. Due to the rapid transmission of the disease and the lack of definitive treatment, countries have employed nonpharmaceutical interventions. This study aimed to investigate the effectiveness of the smart travel ban policy, which has been implemented for non-commercial vehicles in the intercity highways of Iran since November 21, 2020. The other goal was to suggest efficient COVID-19 forecasting tools and to examine the association of intercity travel patterns and COVID-19 trends in Iran. To this end, weekly confirmed cases and deaths due to COVID-19 and the intercity traffic flow reported by loop detectors were aggregated at the country's level. The Box-Jenkins methodology was employed to evaluate the policy's effectiveness, using the interrupted time series analysis. The results indicated that the autoregressive integrated moving average with explanatory variable (ARIMAX) model outperformed the univariate ARIMA model in predicting the disease trends based on the MAPE criterion. The weekly intercity traffic and its lagged variables were entered as covariates in both models of the disease cases and deaths. The results indicated that the weekly intercity traffic increases the new weekly COVID-19 cases and deaths with a time lag of two and five weeks, respectively. Besides, the interrupted time series analysis indicated that the smart travel ban policy had decreased intercity travel by around 29%. Nonetheless, it had no significant direct effect on COVID-19 trends. This study suggests that the travel ban policy would not be efficient lonely unless it is coupled with active measures and adherence to health protocols by the people.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , COVID-19/prevention & control , Iran/epidemiology , Travel , Forecasting , Policy
19.
Lancet ; 395(10227): 871-877, 2020 03 14.
Article in English | MEDLINE | ID: covidwho-2076860

ABSTRACT

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) epidemic has spread from China to 25 countries. Local cycles of transmission have already occurred in 12 countries after case importation. In Africa, Egypt has so far confirmed one case. The management and control of COVID-19 importations heavily rely on a country's health capacity. Here we evaluate the preparedness and vulnerability of African countries against their risk of importation of COVID-19. METHODS: We used data on the volume of air travel departing from airports in the infected provinces in China and directed to Africa to estimate the risk of importation per country. We determined the country's capacity to detect and respond to cases with two indicators: preparedness, using the WHO International Health Regulations Monitoring and Evaluation Framework; and vulnerability, using the Infectious Disease Vulnerability Index. Countries were clustered according to the Chinese regions contributing most to their risk. FINDINGS: Countries with the highest importation risk (ie, Egypt, Algeria, and South Africa) have moderate to high capacity to respond to outbreaks. Countries at moderate risk (ie, Nigeria, Ethiopia, Sudan, Angola, Tanzania, Ghana, and Kenya) have variable capacity and high vulnerability. We identified three clusters of countries that share the same exposure to the risk originating from the provinces of Guangdong, Fujian, and the city of Beijing, respectively. INTERPRETATION: Many countries in Africa are stepping up their preparedness to detect and cope with COVID-19 importations. Resources, intensified surveillance, and capacity building should be urgently prioritised in countries with moderate risk that might be ill-prepared to detect imported cases and to limit onward transmission. FUNDING: EU Framework Programme for Research and Innovation Horizon 2020, Agence Nationale de la Recherche.


Subject(s)
Civil Defense , Coronavirus Infections , Epidemics/prevention & control , Health Resources , Models, Theoretical , Pneumonia, Viral , Population Surveillance , Vulnerable Populations , Africa/epidemiology , COVID-19 , China/epidemiology , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Health Planning , Humans , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , Risk Assessment , Travel
20.
Curr Opin Pulm Med ; 28(3): 192-198, 2022 05 01.
Article in English | MEDLINE | ID: covidwho-2077951

ABSTRACT

PURPOSE OF REVIEW: Mass gathering (MG) religious events provide ideal conditions for transmission and globalization of respiratory tract infections (RTIs). We review recent literature on COVID-19 and other RTIs at recurring international annual MG religious and sporting events. RECENT FINDINGS: Due to the COVID-19 pandemic organizers of MG religious and sporting events introduced risk-based infection control measures that limited transmission of RTIs. The 2020 and 2021 Hajj were conducted with limited numbers of pilgrims compared to the annual millions of pilgrims. The Tokyo 2020 Olympic and Paralympic Games were cancelled and held in 2021. The success of the COVID-19 countermeasures at the 2021 Hajj and 2021 Tokyo Olympics was based on implementing good public health and social measures alongside a comprehensive testing strategy. SUMMARY: MG events are associated with transmission of a range of bacterial and viral RTIs. Introducing risk based a multitude of public health interventions can reduce transmission of SARS-CoV-2 and other RTIs.


Subject(s)
COVID-19 , Respiratory Tract Infections , COVID-19/epidemiology , COVID-19/prevention & control , Humans , Islam , Mass Gatherings , Pandemics/prevention & control , Respiratory Tract Infections/epidemiology , Respiratory Tract Infections/prevention & control , SARS-CoV-2 , Travel
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