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1.
PLoS Comput Biol ; 17(1): e1008609, 2021 01.
Artículo en Inglés | MEDLINE | ID: mdl-33513139

RESUMEN

A key parameter in epidemiological modeling which characterizes the spread of an infectious disease is the generation time, or more generally the distribution of infectiousness as a function of time since infection. There is increasing evidence supporting a prolonged viral shedding window for COVID-19, but the transmissibility in this phase is unclear. Based on this, we develop a generalized Susceptible-Exposed-Infected-Resistant (SEIR) model including an additional compartment of chronically infected individuals who can stay infectious for a longer duration than the reported generation time, but with infectivity reduced to varying degrees. Using the incidence and fatality data from different countries, we first show that such an assumption also yields a plausible model in explaining the data observed prior to the easing of the lockdown measures (relaxation). We then test the predictive power of this model for different durations and levels of prolonged infectiousness using the incidence data after the introduction of relaxation in Switzerland, and compare it with a model without the chronically infected population to represent the models conventionally used. We show that in case of a gradual easing on the lockdown measures, the predictions of the model including the chronically infected population vary considerably from those obtained under a model in which prolonged infectiousness is not taken into account. Although the existence of a chronically infected population still remains largely hypothetical, we believe that our results provide tentative evidence to consider a chronically infected population as an alternative modeling approach to better interpret the transmission dynamics of COVID-19.


Asunto(s)
Control de Enfermedades Transmisibles , Modelos Estadísticos , Esparcimiento de Virus/fisiología , /epidemiología , /transmisión , Control de Enfermedades Transmisibles/métodos , Control de Enfermedades Transmisibles/estadística & datos numéricos , Biología Computacional , Humanos , Suiza
2.
BMJ Glob Health ; 5(12)2020 12.
Artículo en Inglés | MEDLINE | ID: mdl-33355265

RESUMEN

OBJECTIVE: To generate rankings of 35 countries from all continents (except Africa) on performance against COVID-19. DESIGN: International time series, cross-sectional analysis. SELECTED COUNTRIES: Countries having 5500 or more cases (collectively including 85% of the world's cases) as of 16 April 2020 and that had reached 135 days into their pandemic by 30 July. MAIN OUTCOME MEASURES: The initial severity and late-pandemic performance of countries can reasonably be ranked by COVID-19 cases or deaths per million population. For guiding policy and informing public accountability during the pandemic, we propose mid-pandemic performance rankings based on doubling time in days of the total number of cases and deaths in a country. Rank orderings then follow. RESULTS: At day 25 into a country's pandemic, cross-country performance variation was modest: in most countries, cumulative deaths doubled in fewer than 5 days. By day 65, and even more so by day 135, great cross-country variation emerged. By day 135, 9 of the 10 top-performing countries on deaths were European, although they were initially hard hit by the pandemic. Thus, rankings change rapidly enough to point to the value of a dynamic indicator. Five countries-Brazil, Mexico, India, Indonesia and Israel-were among the seven poorest performers at day 135 on both cases and deaths. Doubling times for cases and for deaths are positively correlated, but differ sufficiently to point to the value of both indicators. CONCLUSIONS: Readily available data support transparently generated rankings of countries' performance against COVID-19 based on doubling times of cases and deaths. It is premature to judge the value of these rankings in practice, but the potential and early experience suggest they might help facilitate identification of good policies and inform judgements on national leadership.


Asunto(s)
Control de Enfermedades Transmisibles/normas , Países Desarrollados/clasificación , Pandemias/prevención & control , Control de Enfermedades Transmisibles/estadística & datos numéricos , Estudios Transversales , Humanos
3.
Sci Rep ; 10(1): 22123, 2020 12 17.
Artículo en Inglés | MEDLINE | ID: mdl-33335107

RESUMEN

We established a stochastic individual-based model and simulated the whole process of occurrence, development, and control of the coronavirus disease epidemic and the infectors and patients leaving Hubei Province before the traffic was closed in China. Additionally, the basic reproduction number (R0) and number of infectors and patients who left Hubei were estimated using the coordinate descent algorithm. The median R0 at the initial stage of the epidemic was 4.97 (95% confidence interval [CI] 4.82-5.17). Before the traffic lockdown was implemented in Hubei, 2000 (95% CI 1982-2030) infectors and patients had left Hubei and traveled throughout the country. The model estimated that if the government had taken prevention and control measures 1 day later, the cumulative number of laboratory-confirmed patients in the whole country would have increased by 32.1%. If the lockdown of Hubei was imposed 1 day in advance, the cumulative number of laboratory-confirmed patients in other provinces would have decreased by 7.7%. The stochastic model could fit the officially issued data well and simulate the evolution process of the epidemic. The intervention measurements nationwide have effectively curbed the human-to-human transmission of severe acute respiratory syndrome coronavirus 2.


Asunto(s)
/epidemiología , /transmisión , Número Básico de Reproducción , China/epidemiología , Control de Enfermedades Transmisibles/estadística & datos numéricos , Epidemias , Humanos , Viaje/estadística & datos numéricos
4.
Sci Rep ; 10(1): 22134, 2020 12 17.
Artículo en Inglés | MEDLINE | ID: mdl-33335243

RESUMEN

Spectral analysis characterises oscillatory time series behaviours such as cycles, but accurate estimation requires reasonable numbers of observations. At the time of writing, COVID-19 time series for many countries are short: pre- and post-lockdown series are shorter still. Accurate estimation of potentially interesting cycles seems beyond reach with such short series. We solve the problem of obtaining accurate estimates from short series by using recent Bayesian spectral fusion methods. We show that transformed daily COVID-19 cases for many countries generally contain three cycles operating at wavelengths of around 2.7, 4.1 and 6.7 days (weekly) and that shorter wavelength cycles are suppressed after lockdown. The pre- and post-lockdown differences suggest that the weekly effect is at least partly due to non-epidemic factors. Unconstrained, new cases grow exponentially, but the internal cyclic structure causes periodic declines. This suggests that lockdown success might only be indicated by four or more daily falls. Spectral learning for epidemic time series contributes to the understanding of the epidemic process and can help evaluate interventions. Spectral fusion is a general technique that can fuse spectra recorded at different sampling rates, which can be applied to a wide range of time series from many disciplines.


Asunto(s)
/epidemiología , Control de Enfermedades Transmisibles/estadística & datos numéricos , Cuarentena/estadística & datos numéricos , Teorema de Bayes , Control de Enfermedades Transmisibles/métodos , Humanos , Aislamiento Social
6.
BMC Public Health ; 20(1): 1925, 2020 Dec 29.
Artículo en Inglés | MEDLINE | ID: mdl-33372608

RESUMEN

BACKGROUND: Currently, the novel coronavirus or COVID-19 pandemic poses the greatest global health threat worldwide, and India is no exception. As an overpopulated developing country, it is very difficult to maintain social distancing to restrict the spread of the disease in India. Under these circumstances, it is necessary to examine India's interstate performances to combat COVID-19. This study aims to explore twin objectives: to investigate the comparative efficiency of Indian states to combat COVID-19 and to unfold the factors responsible for interstate disparities in the efficiency in combatting COVID-19. METHODS: The stochastic production frontier model was utilized for data analysis. The empirical analysis was facilitated by the inefficiency effects model, revealing the factors that influence interstate variability in disease management efficiency. Three types of variables, namely, output, inputs, and exogenous, were used to measure health system efficiency. The relevant variables were compiled from secondary sources. The recovery rate from COVID-19 was the output variable and health infrastructures were considered as the input variable. On the contrary, the non-health determinants considered to have a strong influence on the efficiency of states' disease management, but could not be considered as input variables, were recognised as exogenous variables. These exogenous variables were specifically used for the inefficiency analysis. RESULTS: The empirical results demonstrated the existence of disparities across Indian states in the level of efficiency in combatting COVID-19. A non-trivial outcome of this study was that Tamil Nadu was the best performer and Manipur was the worst performer of the investigated states. Variables such as elderly people, sex ratio, literacy rate, population density, influenced the efficiency of states, and thus, affected the recovery rate. CONCLUSION: This study argues for the efficient utilisation of the existing health infrastructures in India. Simultaneously, the study suggests improving the health infrastructure to achieve a long-run benefit.


Asunto(s)
/epidemiología , Control de Enfermedades Transmisibles/estadística & datos numéricos , Utilización de Instalaciones y Servicios/estadística & datos numéricos , Disparidades en Atención de Salud/estadística & datos numéricos , /prevención & control , Geografía , Humanos , India/epidemiología , Densidad de Población , Procesos Estocásticos
7.
BMJ Open ; 10(11): e043560, 2020 11 03.
Artículo en Inglés | MEDLINE | ID: mdl-33148769

RESUMEN

OBJECTIVE: To investigate the influence of demographic and socioeconomic factors on the COVID-19 case-fatality rate (CFR) globally. DESIGN: Publicly available register-based ecological study. SETTING: Two hundred and nine countries/territories in the world. PARTICIPANTS: Aggregated data including 10 445 656 confirmed COVID-19 cases. PRIMARY AND SECONDARY OUTCOME MEASURES: COVID-19 CFR and crude cause-specific death rate were calculated using country-level data from the Our World in Data website. RESULTS: The average of country/territory-specific COVID-19 CFR is about 2%-3% worldwide and higher than previously reported at 0.7%-1.3%. A doubling in size of a population is associated with a 0.48% (95% CI 0.25% to 0.70%) increase in COVID-19 CFR, and a doubling in the proportion of female smokers is associated with a 0.55% (95% CI 0.09% to 1.02%) increase in COVID-19 CFR. The open testing policies are associated with a 2.23% (95% CI 0.21% to 4.25%) decrease in CFR. The strictness of anti-COVID-19 measures was not statistically significantly associated with CFR overall, but the higher Stringency Index was associated with higher CFR in higher-income countries with active testing policies (regression coefficient beta=0.14, 95% CI 0.01 to 0.27). Inverse associations were found between cardiovascular disease death rate and diabetes prevalence and CFR. CONCLUSION: The association between population size and COVID-19 CFR may imply the healthcare strain and lower treatment efficiency in countries with large populations. The observed association between smoking in women and COVID-19 CFR might be due to the finding that the proportion of female smokers reflected broadly the income level of a country. When testing is warranted and healthcare resources are sufficient, strict quarantine and/or lockdown measures might result in excess deaths in underprivileged populations. Spatial dependence and temporal trends in the data should be taken into account in global joint strategy and/or policy making against the COVID-19 pandemic.


Asunto(s)
Enfermedades Cardiovasculares/mortalidad , Control de Enfermedades Transmisibles/estadística & datos numéricos , Infecciones por Coronavirus/mortalidad , Diabetes Mellitus/epidemiología , Producto Interno Bruto/estadística & datos numéricos , Neumonía Viral/mortalidad , Densidad de Población , Regresión Espacial , Distribución por Edad , Betacoronavirus , Técnicas de Laboratorio Clínico/estadística & datos numéricos , Infecciones por Coronavirus/diagnóstico , Política de Salud , Indicadores de Salud , Humanos , Esperanza de Vida , Mortalidad , Pandemias , Prevalencia , Fumar/epidemiología , Análisis Espacial
8.
Artículo en Inglés | MEDLINE | ID: mdl-33143076

RESUMEN

This study aimed to descript the Belgian COVID-19 responses process according to the WHO's (World Health Organization) Health Emergency and Disaster Risk Management Framework (Health EDRM Framework) and to present the measures taken and epidemic impact in the different phases of COVID-19 in Belgium. The WHO's EDRM Framework was used for reviewing the Belgian Public health emergency preparedness and responses in the context of COVID-19. Information on the measures taken was collected through the literature review including all government's communication, reports, and scientific papers. All epidemic data were extracted from a national open database managed and published by the Sciensano. Additionally, two authors closely followed the Belgian situation since the beginning of the pandemic and updated the data every day. During the COVID-19 pandemic, the anti-epidemic strategy was mainly to avoid medical resources exceeding the upper limit. Belgium issued a series of emergency decrees to limit the spread of the virus. An existing structure of "federal-region-municipal" as the framework of public health emergency preparedness and response was adapted. The emergency response process in Belgium was divided into four phases: information-evaluation-coordination-decision-making at the region level and the final decision-making at the federal level. Belgium also implemented a phased plan in the process of setting up and lifting the lockdown. However, it was vulnerable in early response, due to the shortage of medical equipment supplies in general, and more particularly for the long term care facilities (LTCFs). Belgium has achieved an intensive cooperation between stakeholders based on an existing multisectoral emergency organization framework. Legislation, medical insurance, and good communication also played a role in limiting the spread of viruses. However, the authorities underestimated the risk of an epidemic and did not take quarantine measures among people suspected affected by SARS-COV-2 in the early stages, resulting in insufficient medical equipment supply and a large number of deaths in the LTCF. The implementation of the lockdown measure in Belgium also encountered obstacles. The lockdown and its exit strategy were both closely related to the pandemic situation and social and economic life. The authorities should strengthen information management, improve the public awareness of the measures, and find out the balance points between the social and economic life and infection control measures.


Asunto(s)
Betacoronavirus , Defensa Civil/organización & administración , Control de Enfermedades Transmisibles/organización & administración , Infecciones por Coronavirus/prevención & control , Pandemias/prevención & control , Neumonía Viral/prevención & control , Cuarentena , Bélgica/epidemiología , Control de Enfermedades Transmisibles/estadística & datos numéricos , Infecciones por Coronavirus/epidemiología , Humanos , Neumonía Viral/epidemiología , Salud Pública
9.
PLoS One ; 15(10): e0240013, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-33052958

RESUMEN

On March 15, 2020 Puerto Rico implemented non-pharmaceutical interventions (NPIs), including a mandatory curfew, as part of a state of emergency declaration to prevent the community transmission of the SARS-CoV-2 virus. The strict enforcement of this curfew was extended through May 25, with a gradual relaxation beginning on May 1. This report summarizes an assessment of these early mitigation measures on the progression of the COVID-19 pandemic in the island. From March 15 to May 15, 2020, 70,656 results of molecular (RT-PCR) tests were reported to the Puerto Rico Department of Health. Of these, 1,704 were positive, corresponding to 1,311 individuals with COVID-19 included in the study. We derived the epidemic growth rates (r) and the corresponding reproductive numbers (R) from the epidemic curve of these 1,311 individuals with laboratory-confirmed diagnosis of COVID-19 using their date of test collection as a proxy for symptoms onset. Through May 31, 2020, there were 143 COVID-19 associated deaths in Puerto Rico, for a case fatality risk of 10.9%. We compared the observed cases and deaths with Gompertz model projections had the mitigation measures not been implemented. The number of daily RT-PCR-confirmed cases peaked on March 30 (85 cases), showing a weekly cyclical trend, with lower counts on weekends and a decreasing secular trend since March 30. The initial exponential growth rate (r) was 15.87% (95% CI: 7.59%, 24.15%), corresponding to R of 1.82 (95% CI:1.37, 2.30). After March 30, the r value reverted to an exponential decay rate (negative) of -2.95% (95% CI: -4.99%, -0.92%), corresponding to R of 0.93 (95% CI: 0.86, 0.98). We estimate that, had the initial growth rate been maintained, a total of 6,155 additional COVID-19 cases would have occurred by May 15, with 211 additional COVID-19 deaths by May 31. These findings are consistent with very effective implementation of early NPIs as mitigation measures in Puerto Rico. These results also provide a baseline to assess the impact of the transition from mitigation to subsequent containment stages in Puerto Rico.


Asunto(s)
Técnicas de Laboratorio Clínico/estadística & datos numéricos , Control de Enfermedades Transmisibles/estadística & datos numéricos , Infecciones por Coronavirus/epidemiología , Neumonía Viral/epidemiología , Control de Enfermedades Transmisibles/normas , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/prevención & control , Humanos , Pandemias/prevención & control , Neumonía Viral/prevención & control , Puerto Rico , Gestión de Riesgos
15.
BMJ Glob Health ; 5(10)2020 10.
Artículo en Inglés | MEDLINE | ID: mdl-33028699

RESUMEN

Lockdown measures have been introduced worldwide to contain the transmission of COVID-19. However, the term 'lockdown' is not well-defined. Indeed, WHO's reference to 'so-called lockdown measures' indicates the absence of a clear and universally accepted definition of the term 'lockdown'. We propose a definition of 'lockdown' based on a two-by-two matrix that categorises different communicable disease measures based on whether they are compulsory or voluntary; and whether they are targeted at identifiable individuals or facilities, or whether they are applied indiscriminately to a general population or area. Using this definition, we describe the design, timing and implementation of lockdown measures in nine countries in sub-Saharan Africa: Ghana, Nigeria, South Africa, Sierra Leone, Sudan, Tanzania, Uganda, Zambia and Zimbabwe. While there were some commonalities in the implementation of lockdown across these countries, a more notable finding was the variation in the design, timing and implementation of lockdown measures. We also found that the number of reported cases is heavily dependent on the number of tests carried out, and that testing rates ranged from 2031 to 63 928 per million population up until 7 September 2020. The reported number of COVID-19 deaths per million population also varies (0.4 to 250 up until 7 September 2020), but is generally low when compared with countries in Europe and North America. While lockdown measures may have helped inhibit community transmission, the pattern and nature of the epidemic remains unclear. However, there are signs of lockdown harming health by affecting the functioning of the health system and causing social and economic disruption.


Asunto(s)
Control de Enfermedades Transmisibles , Infecciones por Coronavirus/prevención & control , Pandemias/prevención & control , Neumonía Viral/prevención & control , África del Sur del Sahara , Betacoronavirus , Técnicas de Laboratorio Clínico/estadística & datos numéricos , Control de Enfermedades Transmisibles/métodos , Control de Enfermedades Transmisibles/estadística & datos numéricos , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/epidemiología , Humanos , Neumonía Viral/diagnóstico , Neumonía Viral/epidemiología
17.
BMC Med ; 18(1): 316, 2020 10 05.
Artículo en Inglés | MEDLINE | ID: mdl-33012285

RESUMEN

BACKGROUND: Many low- and middle-income countries have implemented control measures against coronavirus disease 2019 (COVID-19). However, it is not clear to what extent these measures explain the low numbers of recorded COVID-19 cases and deaths in Africa. One of the main aims of control measures is to reduce respiratory pathogen transmission through direct contact with others. In this study, we collect contact data from residents of informal settlements around Nairobi, Kenya, to assess if control measures have changed contact patterns, and estimate the impact of changes on the basic reproduction number (R0). METHODS: We conducted a social contact survey with 213 residents of five informal settlements around Nairobi in early May 2020, 4 weeks after the Kenyan government introduced enhanced physical distancing measures and a curfew between 7 pm and 5 am. Respondents were asked to report all direct physical and non-physical contacts made the previous day, alongside a questionnaire asking about the social and economic impact of COVID-19 and control measures. We examined contact patterns by demographic factors, including socioeconomic status. We described the impact of COVID-19 and control measures on income and food security. We compared contact patterns during control measures to patterns from non-pandemic periods to estimate the change in R0. RESULTS: We estimate that control measures reduced physical contacts by 62% and non-physical contacts by either 63% or 67%, depending on the pre-COVID-19 comparison matrix used. Masks were worn by at least one person in 92% of contacts. Respondents in the poorest socioeconomic quintile reported 1.5 times more contacts than those in the richest. Eighty-six percent of respondents reported a total or partial loss of income due to COVID-19, and 74% reported eating less or skipping meals due to having too little money for food. CONCLUSION: COVID-19 control measures have had a large impact on direct contacts and therefore transmission, but have also caused considerable economic and food insecurity. Reductions in R0 are consistent with the comparatively low epidemic growth in Kenya and other sub-Saharan African countries that implemented similar, early control measures. However, negative and inequitable impacts on economic and food security may mean control measures are not sustainable in the longer term.


Asunto(s)
Control de Enfermedades Transmisibles , Infecciones por Coronavirus , Transmisión de Enfermedad Infecciosa/prevención & control , Relaciones Interpersonales , Pandemias , Neumonía Viral , Adulto , Betacoronavirus , Control de Enfermedades Transmisibles/métodos , Control de Enfermedades Transmisibles/organización & administración , Control de Enfermedades Transmisibles/estadística & datos numéricos , Infecciones por Coronavirus/economía , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/prevención & control , Femenino , Humanos , Kenia/epidemiología , Masculino , Evaluación de Resultado en la Atención de Salud , Pandemias/economía , Pandemias/prevención & control , Neumonía Viral/economía , Neumonía Viral/epidemiología , Neumonía Viral/prevención & control , Pobreza/estadística & datos numéricos , Aislamiento Social , Factores Socioeconómicos , Encuestas y Cuestionarios
18.
Comput Math Methods Med ; 2020: 6397063, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-33101454

RESUMEN

The COVID-19 pandemic has resulted in increasing number of infections and deaths every day. Lack of specialized treatments for the disease demands preventive measures based on statistical/mathematical models. The analysis of epidemiological curve fitting, on number of daily infections across affected countries, provides useful insights on the characteristics of the epidemic. A variety of phenomenological models are available to capture the dynamics of disease spread and growth. The number of daily new infections and cumulative number of infections in COVID-19 over four selected countries, namely, Sri Lanka, Italy, the United States, and Hebei province of China, from the first day of appearance of cases to 2nd July 2020 were used in the study. Gompertz, logistic, Weibull, and exponential growth curves were fitted on the cumulative number of infections across countries. AIC, BIC, RMSE, and R 2 were used to determine the best fitting curve for each country. Results revealed that the most appropriate growth curves for Sri Lanka, Italy, the United States, and China (Hebei) are the logistic, Gompertz, Weibull, and Gompertz curves, respectively. Country-wise, overall growth rate, final epidemic size, and short-term forecasts were evaluated using the selected model. Daily log incidences in each country were regressed before and after the identified peak time of the respective outbreak of epidemic. Hence, doubling time/halving time together with daily growth rates and predictions was estimated. Findings and relevant interpretations demonstrate that the outbreak seems to be extinct in Hebei, China, whereas further transmissions are possible in the United States. In Italy and Sri Lanka, current outbreaks transmit in a decreasing rate.


Asunto(s)
Betacoronavirus , Infecciones por Coronavirus/epidemiología , Modelos Estadísticos , Pandemias/estadística & datos numéricos , Neumonía Viral/epidemiología , China/epidemiología , Control de Enfermedades Transmisibles/métodos , Control de Enfermedades Transmisibles/estadística & datos numéricos , Biología Computacional , Infecciones por Coronavirus/prevención & control , Infecciones por Coronavirus/transmisión , Epidemias/prevención & control , Epidemias/estadística & datos numéricos , Predicción , Humanos , Incidencia , Italia/epidemiología , Modelos Logísticos , Conceptos Matemáticos , Pandemias/prevención & control , Neumonía Viral/prevención & control , Neumonía Viral/transmisión , Sri Lanka/epidemiología , Factores de Tiempo , Estados Unidos/epidemiología
19.
BMJ Open ; 10(9): e042867, 2020 09 29.
Artículo en Inglés | MEDLINE | ID: mdl-32994262

RESUMEN

OBJECTIVES: To determine any change in referral patterns and outcomes in children (0-18) referred for child protection medical examination (CPME) during the COVID-19 pandemic compared with previous years. DESIGN: Retrospective observational study, analysing routinely collected clinical data from CPME reports in a rapid response to the pandemic lockdown. SETTING: Birmingham Community Healthcare NHS Trust, which provides all routine CPME for Birmingham, England, population 1.1 million including 288 000 children. PARTICIPANTS: Children aged under 18 years attending CPME during an 18-week period from late February to late June during the years 2018-2020. MAIN OUTCOME MEASURES: Numbers of referrals, source of disclosure and outcomes from CPME. RESULTS: There were 78 CPME referrals in 2018, 75 in 2019 and 47 in 2020, this was a 39.7% (95% CI 12.4% to 59.0%) reduction in referrals from 2018 to 2020, and a 37.3% (95% CI 8.6% to 57.4%) reduction from 2019 to 2020. There were fewer CPME referrals initiated by school staff in 2020, 12 (26%) compared with 36 (47%) and 38 (52%) in 2018 and 2019, respectively. In all years 75.9% of children were known to social care prior to CPME, and 94% of CPME concluded that there were significant safeguarding concerns. CONCLUSIONS: School closure due to COVID-19 may have harmed children as child abuse has remained hidden. There needs to be either mandatory attendance at schools in future or viable alternatives found. There may be a significant increase in safeguarding referrals when schools fully reopen as children disclose the abuse they have experienced at home.


Asunto(s)
Maltrato a los Niños , Servicios de Protección Infantil , Bienestar del Niño , Control de Enfermedades Transmisibles , Infecciones por Coronavirus , Pandemias , Neumonía Viral , Servicios de Salud Escolar/estadística & datos numéricos , Betacoronavirus , Niño , Maltrato a los Niños/prevención & control , Maltrato a los Niños/psicología , Maltrato a los Niños/estadística & datos numéricos , Servicios de Protección Infantil/métodos , Servicios de Protección Infantil/estadística & datos numéricos , Bienestar del Niño/estadística & datos numéricos , Bienestar del Niño/tendencias , Control de Enfermedades Transmisibles/métodos , Control de Enfermedades Transmisibles/estadística & datos numéricos , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/prevención & control , Infecciones por Coronavirus/psicología , Femenino , Humanos , Masculino , Pandemias/prevención & control , Neumonía Viral/epidemiología , Neumonía Viral/prevención & control , Neumonía Viral/psicología , Población , Aislamiento Social , Servicio Social/métodos , Servicio Social/estadística & datos numéricos , Reino Unido/epidemiología
20.
Prev Chronic Dis ; 17: E109, 2020 09 17.
Artículo en Inglés | MEDLINE | ID: mdl-32945766

RESUMEN

INTRODUCTION: In response to the coronavirus disease 2019 (COVID-19) pandemic, New York City closed all nonessential businesses and restricted the out-of-home activities of residents as of March 22, 2020. This order affected different neighborhoods differently, as stores and workplaces are not randomly distributed across the city, and different populations may have responded differently to the out-of-home restrictions. This study examines how the business closures and activity restrictions affected COVID-19 testing results. An evaluation of whether such actions slowed the spread of the pandemic is a crucial step in designing effective public health policies. METHODS: Daily data on the fraction of COVID-19 tests yielding a positive result at the zip code level were analyzed in relation to the number of visits to local businesses (based on smartphone location) and the number of smartphones that stayed fixed at their home location. The regression model also included vectors of fixed effects for the day of the week, the calendar date, and the zip code of residence. RESULTS: A large number of visits to local businesses increased the positivity rate of COVID-19 tests, while a large number of smartphones that stayed at home decreased it. A doubling in the relative number of visits increases the positivity rate by about 12.4 percentage points (95% CI, 5.3 to 19.6). A doubling in the relative number of stay-at-home devices lowered it by 2.0 percentage points (95% CI, -2.9 to -1.2). The business closures and out-of-home activity restrictions decreased the positivity rate, accounting for approximately 25% of the decline observed in April and May 2020. CONCLUSION: Policy measures decreased the likelihood of positive results in COVID-19 tests. These specific policy tools may be successfully used when comparable health crises arise in the future.


Asunto(s)
Betacoronavirus/aislamiento & purificación , Técnicas de Laboratorio Clínico , Comercio/legislación & jurisprudencia , Control de Enfermedades Transmisibles , Infecciones por Coronavirus , Transmisión de Enfermedad Infecciosa , Pandemias , Neumonía Viral , Técnicas de Laboratorio Clínico/métodos , Técnicas de Laboratorio Clínico/estadística & datos numéricos , Control de Enfermedades Transmisibles/instrumentación , Control de Enfermedades Transmisibles/métodos , Control de Enfermedades Transmisibles/estadística & datos numéricos , Infecciones por Coronavirus/diagnóstico , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/prevención & control , Transmisión de Enfermedad Infecciosa/prevención & control , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Humanos , Ciudad de Nueva York/epidemiología , Pandemias/prevención & control , Neumonía Viral/epidemiología , Neumonía Viral/prevención & control , Formulación de Políticas , Gestión de la Salud Poblacional , Salud Pública/métodos , Salud Pública/estadística & datos numéricos , Medición de Riesgo/métodos , Teléfono Inteligente/estadística & datos numéricos
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