Examining geographical disparities in the incubation period of the COVID-19 infected cases in Shenzhen and Hefei, China

BACKGROUND@#Current studies on the COVID-19 depicted a general incubation period distribution and did not examine whether the incubation period distribution varies across patients living in different geographical locations with varying environmental attributes. Profiling the incubation distributions geographically help to determine the appropriate quarantine duration for different regions.@*METHODS@#This retrospective study mainly applied big data analytics and methodology, using the publicly accessible clinical report for patients (n = 543) confirmed as infected in Shenzhen and Hefei, China. Based on 217 patients on whom the incubation period could be identified by the epidemiological method. Statistical and econometric methods were employed to investigate how the incubation distributions varied between infected cases reported in Shenzhen and Hefei.@*RESULTS@#The median incubation period of the COVID-19 for all the 217 infected patients was 8 days (95% CI 7 to 9), while median values were 9 days in Shenzhen and 4 days in Hefei. The incubation period probably has an inverse U-shaped association with the meteorological temperature. The warmer condition in the winter of Shenzhen, average environmental temperature between 10 °C to 15 °C, may decrease viral virulence and result in more extended incubation periods.@*CONCLUSION@#Case studies of the COVID-19 outbreak in Shenzhen and Hefei indicated that the incubation period of COVID-19 had exhibited evident geographical disparities, although the pathological causality between meteorological conditions and incubation period deserves further investigation. Methodologies based on big data released by local public health authorities are applicable for identifying incubation period and relevant epidemiological research.

Tendencias recientes de tasas de mortalidad por edad, sexo, área geográfica y grupos de causas: Chile 1999 -2005 / Recent trends of mortality rates by geographical area, age, sex and broad groups of causes in Chile, 1999-2005

En el marco del monitoreo de las prioridades y desigualdades comunales de salud de Chile, se presentan las tendencias en el país y en cada uno de sus 28 Servicios de Salud, de las tasas de mortalidad infantil, de mortalidad de hombres y de mujeres de 20 a 44 años de edad, y de la mortalidad a los 20-64 años de edad por algunos grandes grupos de causas, para el período 1999-2005.Se miden las desigualdades de las tasas entre los Servicios de Salud para cada año del período, usando el coeficiente de Gini y el rango de variación. Se miden las tendencias de las desigualdades para cada tasa. Se encuentra que en este amplio tramo de edad hubo un descenso de la mortalidad en el país y en la mayoría de los Servicios de Salud, especialmente marcada para la mortalidad por enfermedades respiratorias. También fue importante el descenso de la mortalidad infantil. Las desigualdades entre Servicios fueron más notorias para la mortalidad por enfermedades respiratorias, por causas externas, por cirrosis hepática y por causas mal definidas. La desigualdad aumentó para algunas tasas y disminuyó para otras. Se recomienda seguir midiendo estos indicadores y utilizar la información como guía para mejorar las tendencias en ciertos Servicios y para reducir las desigualdades en ciertos grupos de causas.

In the framework of monitoring communal health priorities and disparities in Chile, we present, for the country and for each of its 28 Health Services, the trends of the following mortality rates for the period 1999-2005: infant mortality, deaths of men and women of ages 20 to 44 years, deaths of men and women of 45 to 64 years, and deaths for some broad groups of causes at ages 20 to 64 years. We measure the between Health Services disparities of the rates for each year of the period, utilizing the Gini coefficient and the range of values. We measure the trends of the disparities for each rate. Findings: in this broad age group there was a descent of mortality in the country and in most of the Health Services. This was more pronounced in the case of mortality from respiratory diseases. There was also an important reduction in infant mortality. The disparities among Health Services were more evident for mortality from respiratory diseases, from external causes, from liver cirrhosis and from ill-defined causes. They increased for some rates and diminished for others. We suggest that these indicators be followed up on a regular annual basis and that the information be used as a guide for efforts to improve the trends in some Services and to reduce the inequities in some groups of causes.