United States Excess Deaths excl COVID: Predicted: Upper Bound: Pennsylvania data was reported at 2,695.000 Number in 16 Sep 2023. This records an increase from the previous number of 2,681.000 Number for 09 Sep 2023. United States Excess Deaths excl COVID: Predicted: Upper Bound: Pennsylvania data is updated weekly, averaging 2,778.500 Number from Jan 2017 (Median) to 16 Sep 2023, with 350 observations. The data reached an all-time high of 3,096.000 Number in 02 Feb 2019 and a record low of 2,541.000 Number in 22 Jul 2017. United States Excess Deaths excl COVID: Predicted: Upper Bound: Pennsylvania data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under Global Database’s United States – Table US.G012: Number of Excess Deaths: by States: All Causes excluding COVID-19: Predicted (Discontinued).

United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Pennsylvania data was reported at 2,554.000 Number in 16 Sep 2023. This records an increase from the previous number of 2,545.000 Number for 09 Sep 2023. United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Pennsylvania data is updated weekly, averaging 2,620.500 Number from Jan 2017 (Median) to 16 Sep 2023, with 350 observations. The data reached an all-time high of 2,938.000 Number in 09 Feb 2019 and a record low of 2,399.000 Number in 22 Jul 2017. United States Excess Deaths excl COVID: Predicted: Avg No. of Deaths: Pennsylvania data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under Global Database’s United States – Table US.G012: Number of Excess Deaths: by States: All Causes excluding COVID-19: Predicted (Discontinued).

Graph and download economic data for Age-Adjusted Premature Death Rate for Berks County, PA (CDC20N2UAA042011) from 1999 to 2019 about Berks County, PA; Reading; premature; death; PA; Prosperity Scorecard; rate; and USA.

United States Excess Deaths: Predicted: Avg Expected No. of Deaths: Pennsylvania data was reported at 2,554.000 Number in 16 Sep 2023. This records an increase from the previous number of 2,545.000 Number for 09 Sep 2023. United States Excess Deaths: Predicted: Avg Expected No. of Deaths: Pennsylvania data is updated weekly, averaging 2,620.500 Number from Jan 2017 (Median) to 16 Sep 2023, with 350 observations. The data reached an all-time high of 2,938.000 Number in 09 Feb 2019 and a record low of 2,399.000 Number in 22 Jul 2017. United States Excess Deaths: Predicted: Avg Expected No. of Deaths: Pennsylvania data remains active status in CEIC and is reported by Centers for Disease Control and Prevention. The data is categorized under Global Database’s United States – Table US.G011: Number of Excess Deaths: by States: All Causes: Predicted (Discontinued).

Premature Death Rate for Clearfield County, PA was 512.70000 Rate per 100,000 in January of 2020, according to the United States Federal Reserve. Historically, Premature Death Rate for Clearfield County, PA reached a record high of 555.20000 in January of 2019 and a record low of 419.70000 in January of 2004. Trading Economics provides the current actual value, an historical data chart and related indicators for Premature Death Rate for Clearfield County, PA - last updated from the United States Federal Reserve on July of 2025.

Premature Death Rate for Greene County, PA was 652.20000 Rate per 100,000 in January of 2020, according to the United States Federal Reserve. Historically, Premature Death Rate for Greene County, PA reached a record high of 690.10000 in January of 2019 and a record low of 407.30000 in January of 2007. Trading Economics provides the current actual value, an historical data chart and related indicators for Premature Death Rate for Greene County, PA - last updated from the United States Federal Reserve on July of 2025.

Premature Death Rate for Bradford County, PA was 523.20000 Rate per 100,000 in January of 2020, according to the United States Federal Reserve. Historically, Premature Death Rate for Bradford County, PA reached a record high of 554.30000 in January of 2019 and a record low of 382.70000 in January of 1999. Trading Economics provides the current actual value, an historical data chart and related indicators for Premature Death Rate for Bradford County, PA - last updated from the United States Federal Reserve on August of 2025.

A new interactive study was conducted using all fatal highway collision data in Pennsylvania from 2015 to 2017 in order to determine the deadliest road stretches in the state of Pennsylvania.

Age-Adjusted Premature Death Rate for Adams County, PA was 319.80000 Rate per 100,000 in January of 2020, according to the United States Federal Reserve. Historically, Age-Adjusted Premature Death Rate for Adams County, PA reached a record high of 361.90000 in January of 1999 and a record low of 260.50000 in January of 2019. Trading Economics provides the current actual value, an historical data chart and related indicators for Age-Adjusted Premature Death Rate for Adams County, PA - last updated from the United States Federal Reserve on July of 2025.

Age-Adjusted Premature Death Rate for Northumberland County, PA was 442.30000 Rate per 100,000 in January of 2020, according to the United States Federal Reserve. Historically, Age-Adjusted Premature Death Rate for Northumberland County, PA reached a record high of 451.30000 in January of 2019 and a record low of 332.30000 in January of 2009. Trading Economics provides the current actual value, an historical data chart and related indicators for Age-Adjusted Premature Death Rate for Northumberland County, PA - last updated from the United States Federal Reserve on July of 2025.

Purpose: This systematic review and meta-analysis investigated the association between Physical activity (PA) before Coronavirus Disease 2019 (COVID-19) infection and the severity of illness and mortality in COVID-19 patients.Methods: A comprehensive search was undertaken to identify retrospective and nonrandomized controlled trial studies comparing the severity and mortality of COVID-19 infection among COVID-19 patients who had previously reported their participation in PA with those who had not. The databases searched were PubMed, Cochrane Library, Scopus, Science Direct, EMBASE, OPENGREY.EU, and ClinicalTrials.gov. The risk of bias was assessed using the Newcastle-Ottawa Scale. A random-effects model was used for determining pairwise meta-analyses. The protocol was registered with PROSPERO (CRD42021262548).Results: Eighteen studies met the inclusion criteria (5 cross-sectional, 12 cohort, and 1 case-control studies). All 1 618 680 subjects were adults. PA significantly decreased the risk of death in COVID-19 patients (odds ratio [OR] 0.34; 95% confidence interval [CI], 0.19–0.62; p < 0.001) and the risk of severe outcomes (OR 0.60; 95% CI, 0.48–0.76; p < 0.001). Subgroup analysis showed that PA for ≥150 min/wk at a moderate intensity or ≥75 min/wk at a vigorous intensity reduced the risks of severity and mortality. Vigorous PA reduced mortality risk, whereas moderate to vigorous PA reduced the risks of severity and mortality.Conclusion: PA before infection might reduce severity and mortality in COVID-19 patients, especially PA ≥ 150 min/wk of moderate activity or ≥75 min/wk of vigorous activity. However, careful interpretations should be considered due to the difference in PA patterns and severity definitions among included studies. This finding implies that engaging in regular PA, even in different patterns, has beneficial effects on the severity and mortality of COVID-19 patients.

BackgroundThere are few studies investigating the relationship between serum vitamin B6 and mortality risk in the elderly. This study hereby evaluated the associations between biomarkers of serum vitamin B6 status and cardiovascular, cancer, and all-cause mortality risks in the elderly.MethodsOur study included a total of 4,881 participants aged 60 years or older from the National Health and Nutrition Examination Survey (NHANES) 2005-2010. Serum vitamin B6 status was estimated based on levels of pyridoxal 5’-phosphate (PLP), 4-pyridoxic acid (4-PA), and vitamin B6 turnover rate (4-PA/PLP) detected by high-performance liquid chromatography. Survival status and corresponding causes of death were matched through the National Death Index records through December 31, 2019. Multivariate Cox regression model was adopted to assess the relationships between serum vitamin B6 status and the risk of mortality.ResultsDuring a median follow-up period of 10.33 years, 507 cardiovascular deaths, 426 cancer deaths, and 1995 all-cause deaths were recorded, respectively. In the multivariate-adjusted Cox model, the hazard ratios (HRs) and 95% confidence intervals (CIs) for the highest versus the lowest quartiles of PLP, 4-PA, and 4-PA/PLP were 0.70(0.54-0.90), 1.33(0.88-2.02), and 2.01(1.41-2.79) for cardiovascular mortality, 0.73(0.52-1.02), 1.05(0.71-1.57), and 1.95(1.25-3.05) for cancer mortality, and 0.62(0.53-0.74), 1.05(0.82-1.34), and 2.29(1.87-2.79) for all-cause mortality, respectively.ConclusionOur study found that lower serum PLP levels were associated with increased risks of cardiovascular and all-cause mortality among the elderly population. And higher vitamin B6 turnover rate was associated with increased risks of cardiovascular, cancer, and all-cause mortality.

There is a lack of sufficient information on the impact of physical activity (PA) and dietary quality (DQ) on mortality in patients with chronic kidney disease (CKD), and no study has yet examined the relationship between the combined effects of PA and DQ on the risk of death in patients with CKD in a representative adult population. Adult CKD patients (n = 6,504) from the National Health and Nutrition Examination Survey (NHANES) 1999–2018 were included in the study. Mortality outcomes were assessed by National Death Index records before 2/25/2019. Four lifestyle categories were established: low-PA individuals with unhealthy diets, low-PA individuals with healthy diets, high-PA individuals with unhealthy diets, and high-PA individuals with healthy diets. Cox proportional risk modeling was used to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs) of various lifestyle categories for all-cause and CVD mortality. During a median follow-up period of 111 months, 1,971 participants with CKD died from all-cause mortality, and 567 died from CVD among 6,504 respondents. The high-PA CKD population with a healthier diet had a significantly lower risk of all-cause [0.75, 95% CI (0.64–0.87)] and CVD [0.69, 95% CI (0.51–0.93)] mortality than the low-PA, unhealthy diet participants did. The age and race subgroups showed significant interactions, with the older (≥60 years) and non-Hispanic black subgroups experiencing a more favorable risk-lowering effect for all-cause death. CKD patients with healthy diets and adequate PA had lower risks of CVD and all-cause mortality than did low-PA individuals with unhealthy diets.

Panama PA: Number of Deaths Ages 15-19 Years data was reported at 235.000 Person in 2019. This records a decrease from the previous number of 253.000 Person for 2018. Panama PA: Number of Deaths Ages 15-19 Years data is updated yearly, averaging 271.500 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 357.000 Person in 2011 and a record low of 235.000 Person in 2019. Panama PA: Number of Deaths Ages 15-19 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Health Statistics. Number of deaths of adolescents ages 15-19 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

Panama PA: Number of Deaths Ages 5-9 Years data was reported at 103.000 Person in 2019. This records a decrease from the previous number of 106.000 Person for 2018. Panama PA: Number of Deaths Ages 5-9 Years data is updated yearly, averaging 126.500 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 154.000 Person in 1990 and a record low of 103.000 Person in 2019. Panama PA: Number of Deaths Ages 5-9 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Health Statistics. Number of deaths of children ages 5-9 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

BackgroundIt is well documented that moderate-to-vigorous intensity physical activity (MVPA) is effective in the prevention of major chronic diseases. Even though the current international physical activity (PA) guidelines still mainly focus on MVPA, the topic of the most recent epidemiological studies has shifted from MVPA to light intensity physical activity (LPA), owing to the necessity of promoting all activities vs. sedentary behavior (SB). However, the evidence remains currently limited. Thus, the clarification of the effects of LPA and the close relationship with SB is crucial to promote public health.MethodPA and SB were assessed by a validated self-administered questionnaire (POPAQ) investigating 5 different types of PA during the 7 previous days. PA was measured in metabolic equivalent of task (MET)-h, which refers to the amount of energy (calories) expended per hour of PA. SB was measured in hour/day. Medical histories and examinations were taken during each clinical visit to determine clinical events. All-cause mortality was established using the same procedure and by checking local death registries. The relationships between the intensity of PA (light, moderate to vigorous) and mortality and between the periods of SB and mortality or CV events were analyzed by splines and COX models, adjusted for sex and year of birth.ResultsFrom the 1011 65-year-old subjects initially included in 2001 (60% women), the last 18-year follow-up has been currently completed since 2019. A total of 197 deaths (19.2%, including 77 CV deaths) and 195 CV events (19.3%) were reported. Averages (standard deviation) of MVPA, LPA and SB were, respectively, 1.2 h/d (0.3), 5.8 h/d (1.1), and 6.6 h/d (2.3). For all-cause deaths, as well as CV deaths, the splines were significant for LPA (p = 0.04 and p = 0.01), and MVPA (p 

Panama PA: Number of Deaths Ages 10-14 Years data was reported at 120.000 Person in 2019. This records a decrease from the previous number of 122.000 Person for 2018. Panama PA: Number of Deaths Ages 10-14 Years data is updated yearly, averaging 124.500 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 130.000 Person in 2012 and a record low of 119.000 Person in 2005. Panama PA: Number of Deaths Ages 10-14 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Health Statistics. Number of deaths of adolescents ages 10-14 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.

The COVID-19 community levels were developed using a combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days. The COVID-19 community level was determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.

Using these data, the COVID-19 community level was classified as low, medium, or high.

COVID-19 Community Levels were used to help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals.

For the most accurate and up-to-date data for any county or state, visit the relevant health department website. COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.

Archived Data Notes:

This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.

March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.

March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.

March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.

March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.

March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).

March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.

April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.

April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials to verify the data submitted, as other data systems are not providing alerts for substantial increases in disease transmission or severity in the state.

May 26, 2022: COVID-19 Community Level (CCL) data released for McCracken County, KY for the week of May 5, 2022 have been updated to correct a data processing error. McCracken County, KY should have appeared in the low community level category during the week of May 5, 2022. This correction is reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for several Florida counties for the week of May 19th, 2022, have been corrected for a data processing error. Of note, Broward, Miami-Dade, Palm Beach Counties should have appeared in the high CCL category, and Osceola County should have appeared in the medium CCL category. These corrections are reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for Orange County, New York for the week of May 26, 2022 displayed an erroneous case rate of zero and a CCL category of low due to a data source error. This county should have appeared in the medium CCL category.

June 2, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a data processing error. Tolland County, CT should have appeared in the medium community level category during the week of May 26, 2022. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a misspelling. The medium community level category for Tolland County, CT on the week of May 26, 2022 was misspelled as “meduim” in the data set. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Mississippi counties for the week of June 9, 2022 should be interpreted with caution due to a reporting cadence change over the Memorial Day holiday that resulted in artificially inflated case rates in the state.

July 7, 2022: COVID-19 Community Level (CCL) data released for Rock County, Minnesota for the week of July 7, 2022 displayed an artificially low case rate and CCL category due to a data source error. This county should have appeared in the high CCL category.

July 14, 2022: COVID-19 Community Level (CCL) data released for Massachusetts counties for the week of July 14, 2022 should be interpreted with caution due to a reporting cadence change that resulted in lower than expected case rates and CCL categories in the state.

July 28, 2022: COVID-19 Community Level (CCL) data released for all Montana counties for the week of July 21, 2022 had case rates of 0 due to a reporting issue. The case rates have been corrected in this update.

July 28, 2022: COVID-19 Community Level (CCL) data released for Alaska for all weeks prior to July 21, 2022 included non-resident cases. The case rates for the time series have been corrected in this update.

July 28, 2022: A laboratory in Nevada reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate will be inflated in Clark County, NV for the week of July 28, 2022.

August 4, 2022: COVID-19 Community Level (CCL) data was updated on August 2, 2022 in error during performance testing. Data for the week of July 28, 2022 was changed during this update due to additional case and hospital data as a result of late reporting between July 28, 2022 and August 2, 2022. Since the purpose of this data set is to provide point-in-time views of COVID-19 Community Levels on Thursdays, any changes made to the data set during the August 2, 2022 update have been reverted in this update.

August 4, 2022: COVID-19 Community Level (CCL) data for the week of July 28, 2022 for 8 counties in Utah (Beaver County, Daggett County, Duchesne County, Garfield County, Iron County, Kane County, Uintah County, and Washington County) case data was missing due to data collection issues. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 4, 2022: Due to a reporting cadence change, case rates for all Alabama counties will be lower than expected. As a result, the CCL levels published on August 4, 2022 should be interpreted with caution.

August 11, 2022: COVID-19 Community Level (CCL) data for the week of August 4, 2022 for South Carolina have been updated to correct a data collection error that resulted in incorrect case data. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 18, 2022: COVID-19 Community Level (CCL) data for the week of August 11, 2022 for Connecticut have been updated to correct a data ingestion error that inflated the CT case rates. CDC, in collaboration with CT, has resolved the issue and the correction is reflected in this update.

August 25, 2022: A laboratory in Tennessee reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate may be inflated in many counties and the CCLs published on August 25, 2022 should be interpreted with caution.

August 25, 2022: Due to a data source error, the 7-day case rate for St. Louis County, Missouri, is reported as zero in the COVID-19 Community Level data released on August 25, 2022. Therefore, the COVID-19 Community Level for this county should be interpreted with caution.

September 1, 2022: Due to a reporting issue, case rates for all Nebraska counties will include 6 days of data instead of 7 days in the COVID-19 Community Level (CCL) data released on September 1, 2022. Therefore, the CCLs for all Nebraska counties should be interpreted with caution.

September 8, 2022: Due to a data processing error, the case rate for Philadelphia County, Pennsylvania,

Panama PA: Number of Deaths Ages 20-24 Years data was reported at 408.000 Person in 2019. This records a decrease from the previous number of 410.000 Person for 2018. Panama PA: Number of Deaths Ages 20-24 Years data is updated yearly, averaging 395.500 Person from Dec 1990 (Median) to 2019, with 30 observations. The data reached an all-time high of 473.000 Person in 2011 and a record low of 321.000 Person in 1990. Panama PA: Number of Deaths Ages 20-24 Years data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Panama – Table PA.World Bank.WDI: Health Statistics. Number of deaths of youths ages 20-24 years; ; Estimates developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA Population Division) at www.childmortality.org.; Sum; Aggregate data for LIC, UMC, LMC, HIC are computed based on the groupings for the World Bank fiscal year in which the data was released by the UN Inter-agency Group for Child Mortality Estimation.

California reported the largest number of homicides to the FBI in 2023, at 1,929 for the year. Texas recorded the second-highest number of murders, with 1,845 for the year. Homicide victim demographics There were a total of 19,252 reported homicide cases in the U.S. in 2023. When looking at murder victims by gender and ethnicity, the vast majority were male, while just over half of the victims were Black or African American. In addition, homicide victims in the United States were found most likely to be between the ages of 20 and 34 years old, with the majority of victims aged between 17 to 54 years old. Are murders up? In short, no – since the 1990s the number of murders in the U.S. has decreased significantly. In 1990, the murder rate per 100,000 people stood at 9.4, and stood at 5.7 in 2023. It should be noted though that the number of homicides increased slightly from 2014 to 2017, although figures declined again in 2018 and 2019, before ticking up once more in 2020 and 2021. Despite this decline, when viewed in international comparison, the U.S. murder rate is still notably high. For example, the Canadian homicide rate stood at 1.94 in 2023, while the homicide rate in England and Wales was even lower.