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2.
Nat Commun ; 12(1): 1090, 2021 02 17.
Article in English | MEDLINE | ID: covidwho-1087445

ABSTRACT

In response to the COVID-19 pandemic, countries have sought to control SARS-CoV-2 transmission by restricting population movement through social distancing interventions, thus reducing the number of contacts. Mobility data represent an important proxy measure of social distancing, and here, we characterise the relationship between transmission and mobility for 52 countries around the world. Transmission significantly decreased with the initial reduction in mobility in 73% of the countries analysed, but we found evidence of decoupling of transmission and mobility following the relaxation of strict control measures for 80% of countries. For the majority of countries, mobility explained a substantial proportion of the variation in transmissibility (median adjusted R-squared: 48%, interquartile range - IQR - across countries [27-77%]). Where a change in the relationship occurred, predictive ability decreased after the relaxation; from a median adjusted R-squared of 74% (IQR across countries [49-91%]) pre-relaxation, to a median adjusted R-squared of 30% (IQR across countries [12-48%]) post-relaxation. In countries with a clear relationship between mobility and transmission both before and after strict control measures were relaxed, mobility was associated with lower transmission rates after control measures were relaxed indicating that the beneficial effects of ongoing social distancing behaviours were substantial.


Subject(s)
COVID-19/transmission , Communicable Disease Control/methods , Pandemics/prevention & control , SARS-CoV-2/isolation & purification , Algorithms , COVID-19/epidemiology , COVID-19/virology , Communicable Disease Control/statistics & numerical data , Global Health , Humans , Models, Theoretical , Physical Distancing , Quarantine/methods , SARS-CoV-2/physiology
3.
Int J Infect Dis ; 102: 463-471, 2021 Jan.
Article in English | MEDLINE | ID: covidwho-966658

ABSTRACT

OBJECTIVES: In this data collation study, we aimed to provide a comprehensive database describing the epidemic trends and responses during the first wave of coronavirus disease 2019 (COVID-19) throughout the main provinces in China. METHODS: From mid-January to March 2020, we extracted publicly available data regarding the spread and control of COVID-19 from 31 provincial health authorities and major media outlets in mainland China. Based on these data, we conducted descriptive analyses of the epidemic in the six most-affected provinces. RESULTS: School closures, travel restrictions, community-level lockdown, and contact tracing were introduced concurrently around late January but subsequent epidemic trends differed among provinces. Compared with Hubei, the other five most-affected provinces reported a lower crude case fatality ratio and proportion of critical and severe hospitalised cases. From March 2020, as the local transmission of COVID-19 declined, switching the focus of measures to the testing and quarantine of inbound travellers may have helped to sustain the control of the epidemic. CONCLUSIONS: Aggregated indicators of case notifications and severity distributions are essential for monitoring an epidemic. A publicly available database containing these indicators and information regarding control measures is a useful resource for further research and policy planning in response to the COVID-19 epidemic.


Subject(s)
COVID-19/epidemiology , SARS-CoV-2 , COVID-19/prevention & control , China/epidemiology , Contact Tracing , Databases, Factual , Humans
4.
BMC Med ; 18(1): 321, 2020 10 09.
Article in English | MEDLINE | ID: covidwho-840743

ABSTRACT

BACKGROUND: After experiencing a sharp growth in COVID-19 cases early in the pandemic, South Korea rapidly controlled transmission while implementing less stringent national social distancing measures than countries in Europe and the USA. This has led to substantial interest in their "test, trace, isolate" strategy. However, it is important to understand the epidemiological peculiarities of South Korea's outbreak and characterise their response before attempting to emulate these measures elsewhere. METHODS: We systematically extracted numbers of suspected cases tested, PCR-confirmed cases, deaths, isolated confirmed cases, and numbers of confirmed cases with an identified epidemiological link from publicly available data. We estimated the time-varying reproduction number, Rt, using an established Bayesian framework, and reviewed the package of interventions implemented by South Korea using our extracted data, plus published literature and government sources. RESULTS: We estimated that after the initial rapid growth in cases, Rt dropped below one in early April before increasing to a maximum of 1.94 (95%CrI, 1.64-2.27) in May following outbreaks in Seoul Metropolitan Region. By mid-June, Rt was back below one where it remained until the end of our study (July 13th). Despite less stringent "lockdown" measures, strong social distancing measures were implemented in high-incidence areas and studies measured a considerable national decrease in movement in late February. Testing the capacity was swiftly increased, and protocols were in place to isolate suspected and confirmed cases quickly; however, we could not estimate the delay to isolation using our data. Accounting for just 10% of cases, individual case-based contact tracing picked up a relatively minor proportion of total cases, with cluster investigations accounting for 66%. CONCLUSIONS: Whilst early adoption of testing and contact tracing is likely to be important for South Korea's successful outbreak control, other factors including regional implementation of strong social distancing measures likely also contributed. The high volume of testing and the low number of deaths suggest that South Korea experienced a small epidemic relative to other countries. Caution is needed in attempting to replicate the South Korean response in populations with larger more geographically widespread epidemics where finding, testing, and isolating cases that are linked to clusters may be more difficult.


Subject(s)
Betacoronavirus , Contact Tracing/methods , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Quarantine/methods , Bayes Theorem , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques , Contact Tracing/trends , Coronavirus Infections/diagnosis , Disease Outbreaks/prevention & control , Humans , Pneumonia, Viral/diagnosis , Quarantine/trends , Republic of Korea/epidemiology , SARS-CoV-2
5.
Obes Rev ; 21(11): e13128, 2020 11.
Article in English | MEDLINE | ID: covidwho-731029

ABSTRACT

The linkage of individuals with obesity and COVID-19 is controversial and lacks systematic reviews. After a systematic search of the Chinese and English language literature on COVID-19, 75 studies were used to conduct a series of meta-analyses on the relationship of individuals with obesity-COVID-19 over the full spectrum from risk to mortality. A systematic review of the mechanistic pathways for COVID-19 and individuals with obesity is presented. Pooled analysis show individuals with obesity were more at risk for COVID-19 positive, >46.0% higher (OR = 1.46; 95% CI, 1.30-1.65; p < 0.0001); for hospitalization, 113% higher (OR = 2.13; 95% CI, 1.74-2.60; p < 0.0001); for ICU admission, 74% higher (OR = 1.74; 95% CI, 1.46-2.08); and for mortality, 48% increase in deaths (OR = 1.48; 95% CI, 1.22-1.80; p < 0.001). Mechanistic pathways for individuals with obesity are presented in depth for factors linked with COVID-19 risk, severity and their potential for diminished therapeutic and prophylactic treatments among these individuals. Individuals with obesity are linked with large significant increases in morbidity and mortality from COVID-19. There are many mechanisms that jointly explain this impact. A major concern is that vaccines will be less effective for the individuals with obesity.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Coronavirus Infections/physiopathology , Obesity/epidemiology , Obesity/physiopathology , Pneumonia, Viral/epidemiology , Pneumonia, Viral/physiopathology , COVID-19 , Comorbidity , Humans , Internationality , Pandemics , SARS-CoV-2
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