Trend of Health Service Coverage Fact Sheet Fiscal Year 2073/74 Province Level.This data was obtained from Annual Report 2073/74 provided by Department of Health Services.

In 2023, the trend of gross regional domestic product (GRDP) at constant market prices in Central Sulawesi, Indonesia reached ******* index points from the manufacturing sector, indicating a significant increase since the basis year in 2010 whereas the trend was equivalent to 100 index points. Indonesia is one of the world's largest manufacturing countries, and the industry is becoming increasingly important to the country's economy.

Trend of Health Service Coverage Fact Sheet Fiscal Year 2073/74 Province Level.This data was obtained from Annual Report 2073/74 provided by Department of Health Services.

The contents of the dataset are related to the demographic trend in the province of Trento. The data, which come from various sources, were drawn up by the Labour Market and Policy Studies Office for the preparation of the Annual Employment Report in the province of Trento, available as content open to the URL: https://www.agenzialavoro.tn.it/Open-Data/Other-content-available The dataset, including resources in PDF format, is also available on the Employment Agency’s Open Data Portal at the URL: https://www.agenzialavoro.tn.it/Open-Data/I-dataset-available/Population-and-society/Demography-and-population/Demographic Trend/Year-2020 The “time coverage” metadata refers to the time interval taken into account by the Historical Series that are identified in the file name with the suffix _ST. The data released in CSV format are Machine Readable, identified in the file name with the suffix _MR and validated. ATTRIBUTION: Data compiled by the Office of Labour Market and Policy Studies on Istat-ISPAT data.

ObjectiveExploring the Incidence, Epidemic Trends, and Spatial Distribution Characteristics of Sporadic Hepatitis E in Hainan Province from 2013 to 2022 through four major tertiary hospitals in the Province.MethodsWe collected data on confirmed cases of hepatitis E in Hainan residents admitted to the four major tertiary hospitals in Haikou City from January 2013 to December 2022. We used SPSS software to analyze the correlation between incidence rate and economy, population density and geographical location, and origin software to draw a scatter chart and SAS 9.4 software to conduct a descriptive analysis of the time trend. The distribution was analyzed using ArcMap 10.8 software (spatial autocorrelation analysis, hotspot identification, concentration, and dispersion trend analysis). SAS software was used to build an autoregressive integrated moving average model (ARIMA) to predict the monthly number of cases in 2023 and 2024.ResultsFrom 2013 to 2022, 1,922 patients with sporadic hepatitis E were treated in the four hospitals of Hainan Province. The highest proportion of patients (n = 555, 28.88%) were aged 50–59 years. The annual incidence of hepatitis E increased from 2013 to 2019, with a slight decrease in 2020 and 2021 and an increase in 2022. The highest number of cases was reported in Haikou, followed by Dongfang and Danzhou. We found that there was a correlation between the economy, population density, latitude, and the number of cases, with the correlation coefficient |r| value fluctuating between 0.403 and 0.421, indicating a linear correlation. At the same time, a scatter plot shows the correlation between population density and incidence from 2013 to 2022, with r2 values fluctuating between 0.5405 and 0.7116, indicating a linear correlation. Global Moran’s I, calculated through spatial autocorrelation analysis, showed that each year from 2013 to 2022 all had a Moran’s I value >0, indicating positive spatial autocorrelation (p 

Google Mobility Changes: Parks: Italy: Veneto: Province of Treviso data was reported at 48.000 % in 15 Oct 2022. This records a decrease from the previous number of 59.000 % for 14 Oct 2022. Google Mobility Changes: Parks: Italy: Veneto: Province of Treviso data is updated daily, averaging 22.000 % from Feb 2020 (Median) to 15 Oct 2022, with 958 observations. The data reached an all-time high of 342.000 % in 18 Apr 2022 and a record low of -94.000 % in 12 Apr 2020. Google Mobility Changes: Parks: Italy: Veneto: Province of Treviso data remains active status in CEIC and is reported by Google LLC. The data is categorized under Global Database’s Italy – Table IT.Google.GM: Mobility Trends: Parks (Discontinued).

The number of inhabitants according to official statistics per age group of 5 years and gender by administrative entity (region, province, district and municipality) for Flanders and the Brussels Capital Region

Context

To inform citizens and make the collected data available, the Department of Civil Protection has developed an interactive geographic dashboard accessible at the addresses http://arcg.is/C1unv (desktop version) and http://arcg.is/081a51 (mobile version) and makes available, with CC-BY-4.0 license, the following information updated daily at 18:30 (after the Head of Department press conference). For more detail, see https://github.com/pcm-dpc/COVID-19.

Content

COVID-19 data Italy

National trend Json data Provinces data Regions data Summary cards Areas Repository structure COVID-19 / │ ├── national-trend / │ ├── dpc-covid19-eng-national-trend-yyyymmdd.csv ├── areas / │ ├── geojson │ │ ├── dpc-covid19-ita-aree.geojson │ ├── shp │ │ ├── dpc-covid19-eng-areas.shp ├── data-provinces / │ ├── dpc-covid19-ita-province-yyyymmdd.csv ├── data-json / │ ├── dpc-covid19-eng - *. Json ├── data-regions / │ ├── dpc-covid19-eng-regions-yyyymmdd.csv ├── summary-sheets / │ ├── provinces │ │ ├── dpc-covid19-ita-scheda-province-yyyymmdd.pdf │ ├── regions │ │ ├── dpc-covid19-eng-card-regions-yyyymmdd.pdf

Data by Region Directory: data-regions Daily file structure: dpc-covid19-ita-regions-yyyymmdd.csv (dpc-covid19-ita-regions-20200224.csv) Overall file: dpc-covid19-eng-regions.csv An overall JSON file of all dates is made available in the "data-json" folder: dpc-covid19-eng-regions.json

Data by Province Directory: data-provinces Daily file structure: dpc-covid19-ita-province-yyyymmdd.csv (dpc-covid19-ita-province-20200224.csv) Overall file: dpc-covid19-ita-province.csv

Acknowledgements

Banner photo by CDC on Unsplash

Data from https://github.com/pcm-dpc/COVID-19 released under a CC 4.0 license. See https://github.com/pcm-dpc/COVID-19 for more detail.

Google Mobility Changes: Parks: Italy: Veneto: Province of Verona data was reported at 78.000 % in 15 Oct 2022. This records an increase from the previous number of 48.000 % for 14 Oct 2022. Google Mobility Changes: Parks: Italy: Veneto: Province of Verona data is updated daily, averaging 36.000 % from Feb 2020 (Median) to 15 Oct 2022, with 974 observations. The data reached an all-time high of 321.000 % in 18 Apr 2022 and a record low of -96.000 % in 22 Mar 2020. Google Mobility Changes: Parks: Italy: Veneto: Province of Verona data remains active status in CEIC and is reported by Google LLC. The data is categorized under Global Database’s Italy – Table IT.Google.GM: Mobility Trends: Parks (Discontinued).

Population density and area of administrative entities (region, province, district and municipality) for Flanders and the Brussels Capital Region

Number of employees by North American Industry Classification System (NAICS) and data type (seasonally adjusted, trend-cycle and unadjusted), last 5 months. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.

Number of persons in the labour force (employment and unemployment), unemployment rate, participation rate and employment rate by province, gender and age group. Data are presented for 12 months earlier, previous month and current month, as well as year-over-year and month-to-month level change and percentage change. Data are also available for the standard error of the estimate, the standard error of the month-to-month change and the standard error of the year-over-year change.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Objective To analyze the spatiotemporal characteristics of pertussis in Shandong Province.Methods Data on pertussis cases in Shandong Province from 2015 to 2024 were collected from China Information System for Disease Control and Prevention. Using spatiotemporal analysis methods to analyze the spatiotemporal distribution characteristics of pertussis and determine the hotspots of incidence.Results From 2015 to 2024, 46 172 cases of pertussis were reported in Shandong Province, with an average annual incidence rate of about 4.60/100 000. The reported incidence rate showed an overall upward trend, and in 2024, the reported incidence rate reached the highest level in history (19.20/100 000) since the implementation of children planning immunization.The regions with high incidence rate were mainly located in Jinan city, Liaocheng city, Tai'an city, Zibo city, Binzhou city, Jining city, Dezhou city,Zaozhuang city and Dongying city, and mainly in the central and western regions of Shandong Province. The global spatial autocorrelation analysis found that the Moran'I index of incidence rate of pertussis in Shandong Province in each year from 2015 to 2024 was>0.00, showing obvious spatial clustering. Local spatial autocorrelation analysis showed that the "high high" clustering areas were mainly distributed in the central and western regions of Shandong Province, including some counties in Jinan, Liaocheng, Tai'an, Binzhou and Dezhou city, which were hotspots for pertussis incidence in Shandong Province. The spatial trend surface analysis showed that the annual incidence rate of pertussis in each year basically decreased from west to east. In the early stage of the north-south direction, there was a curved trend of low north-south and high in the middle. In the middle and later stages, the northern part was mostly in a higher position, indicating that the central and western regions have always been high-risk areas for pertussis in Shandong Province.Conclusions The incidence of pertussis in Shandong Province from 2015 to 2024 has obvious spatiotemporal clustering, and the central and western regions are key areas for pertussis prevention and control.

The number of inhabitants on January 1 according to the official definition of the population, by administrative entity (region, province, district and municipality) for Flanders and the Brussels Capital Region

Google Mobility Changes: Parks: Italy: Veneto: Province of Rovigo data was reported at 77.000 % in 15 Oct 2022. This records a decrease from the previous number of 92.000 % for 14 Oct 2022. Google Mobility Changes: Parks: Italy: Veneto: Province of Rovigo data is updated daily, averaging 80.000 % from Feb 2020 (Median) to 15 Oct 2022, with 949 observations. The data reached an all-time high of 391.000 % in 15 Aug 2022 and a record low of -76.000 % in 22 Mar 2020. Google Mobility Changes: Parks: Italy: Veneto: Province of Rovigo data remains active status in CEIC and is reported by Google LLC. The data is categorized under Global Database’s Italy – Table IT.Google.GM: Mobility Trends: Parks (Discontinued).

No Publication Abstract is Available

Google Mobility Changes: Parks: Argentina: Salta Province: Metán Department data was reported at 21.000 % in 30 Sep 2022. This records an increase from the previous number of 2.000 % for 29 Sep 2022. Google Mobility Changes: Parks: Argentina: Salta Province: Metán Department data is updated daily, averaging -23.000 % from Feb 2020 (Median) to 30 Sep 2022, with 933 observations. The data reached an all-time high of 181.000 % in 09 Jul 2022 and a record low of -85.000 % in 03 May 2020. Google Mobility Changes: Parks: Argentina: Salta Province: Metán Department data remains active status in CEIC and is reported by Google LLC. The data is categorized under Global Database’s Argentina – Table AR.Google.GM: Mobility Trends: Parks.

Google Mobility Changes: Parks: Vietnam: Kon Tum Province data was reported at 2.000 % in 30 Sep 2022. This records an increase from the previous number of -9.000 % for 29 Sep 2022. Google Mobility Changes: Parks: Vietnam: Kon Tum Province data is updated daily, averaging -37.000 % from Feb 2020 (Median) to 30 Sep 2022, with 934 observations. The data reached an all-time high of 43.000 % in 02 Sep 2022 and a record low of -70.000 % in 11 Sep 2021. Google Mobility Changes: Parks: Vietnam: Kon Tum Province data remains active status in CEIC and is reported by Google LLC. The data is categorized under Global Database’s Vietnam – Table VN.Google.GM: Mobility Trends: Parks.

Google Mobility Changes: Parks: Italy: Veneto: Province of Vicenza data was reported at 89.000 % in 15 Oct 2022. This records an increase from the previous number of 71.000 % for 14 Oct 2022. Google Mobility Changes: Parks: Italy: Veneto: Province of Vicenza data is updated daily, averaging 33.000 % from Feb 2020 (Median) to 15 Oct 2022, with 964 observations. The data reached an all-time high of 321.000 % in 18 Apr 2022 and a record low of -93.000 % in 22 Mar 2020. Google Mobility Changes: Parks: Italy: Veneto: Province of Vicenza data remains active status in CEIC and is reported by Google LLC. The data is categorized under Global Database’s Italy – Table IT.Google.GM: Mobility Trends: Parks (Discontinued).