scholarly journals Predicting Active, Death and Recovery Rates of COVID-19 in Algeria Using Facebook’ Prophet Model

2021 ◽  
Author(s):  
Mohamed LOUNIS
Keyword(s):  
Death Rate ◽  
Rate Increase ◽  
Preventive Measures ◽  
Future Period ◽  
Recovery Rates ◽  
Death Rates ◽  
Rate Decrease

The coronavirus disease pandemic 2019 (COVID-19) has emerged in Wuhan province, China in December 2019 and has spread over all countries. The current study was carried out to predict active, death and cured rate of COVID 19 in Algeria for a future period of 35 days using FB prophet model. Results shoed that the active rate and the death rate decrease for the next days while the cured rate increase. The active, cured and death rates are estimated at 19.7% 78.85% and 2.55% respectively. These results highlight the importance of FB prophet model in COVID-19 prediction which could help national authorities in adopting the best preventive measures.

The impact of climate temperature on counts, recovery, and death rates due to SARS-CoV-2 in South Africa. (Preprint)

2020 ◽  
Author(s):  
Neven Chetty ◽  
Bamise Adeleye ◽  
Abiola Olawale Ilori
Keyword(s):  
South Africa ◽  
South African ◽  
Death Rate ◽  
Western Cape ◽  
Warm Climate ◽  
The South ◽  
Recovery Rates ◽  
Death Rates ◽  
Online Resource ◽  
The Impact

BACKGROUND The impact of climate temperature on the counts (number of positive COVID-19 cases reported), recovery, and death rates of COVID-19 cases in South Africa's nine provinces was investigated. The data for confirmed cases of COVID-19 were collected for March 25 and June 30, 2020 (14 weeks) from South Africa's Government COVID-19 online resource, while the daily provincial climate temperatures were collected from the website of the South African Weather Service. Our result indicates that a higher or lower climate temperature does not prevent or delay the spread and death rates but shows significant positive impacts on the recovery rates of COVID-19 patients. Thus, it indicates that the climate temperature is unlikely to impose a strict limit on the spread of COVID-19. There is no correlation between the cases and death rates, an indicator that no particular temperature range is closely associated with a faster or slower death rate of COVID-19 patients. As evidence from our study, a warm climate temperature can only increase the recovery rate of COVID-19 patients, ultimately impacting the death and active case rates and freeing up resources quicker to enable health facilities to deal with those patients' climbing rates who need treatment. OBJECTIVE This study aims to investigate the impact of climate temperature variation on the counts, recovery, and death rates of COVID-19 cases in all South Africa's provinces. The findings were compared with those of countries with comparable climate temperature values. METHODS The data for confirmed cases of COVID-19 were collected for March 25 and June 30 (14 weeks) for South African provinces, including daily counts, death, and recovery rates. The dates were grouped into two, wherein weeks 1-5 represent the periods of total lockdown to contain the spread of COVID-19 in South Africa. Weeks 6-14 are periods where the lockdown was eased to various levels 4 and 3. The daily information of COVID-19 count, death, and recovery was obtained from South Africa's Government COVID-19 online resource (https://sacoronavirus.co.za). Daily provincial climate temperatures were collected from the website of the South African Weather Service (https://www.weathersa.co.za). The provinces of South Africa are Eastern Cape, Western Cape, Northern Cape, Limpopo, Northwest, Mpumalanga, Free State, KwaZulu-Natal, Western Cape, and Gauteng. Weekly consideration was given to the daily climate temperature (average minimum and maximum). The recorded values were considered, respectively, to be in the ratio of death-to-count (D/C) and recovery-to-count (R/C). Descriptive statistics were performed for all the data collected for this study. The analyses were performed using the Person’s bivariate correlation to analyze the association between climate temperature, death-to-count, and recovery-to-count ratios of COVID-19. RESULTS The results showed that higher climate temperatures aren't essential to avoid the COVID-19 from being spread. The present results conform to the reports that suggested that COVID-19 is unlike the seasonal flu, which does dissipate as the climate temperature rises [17]. Accordingly, the ratio of counts and death-to-count cannot be concluded to be influenced by variations in the climate temperatures within the study areas. CONCLUSIONS The study investigates the impact of climate temperature on the counts, recovery, and death rates of COVID-19 cases in all South Africa's provinces. The findings were compared with those of countries with comparable climate temperatures as South Africa. Our result indicates that a higher or lower climate temperature does not prevent or delay the spread and death rates but shows significant positive impacts on the recovery rates of COVID-19 patients. Warm climate temperatures seem not to restrict the spread of the COVID-19 as the count rate was substantial at every climate temperatures. Thus, it indicates that the climate temperature is unlikely to impose a strict limit on the spread of COVID-19. There is no correlation between the cases and death rates, an indicator that there is no particular temperature range of the climatic conditions closely associated with a faster or slower death rate of COVID-19 patients. However, other shortcomings in this study's process should not be ignored. Some other factors may have contributed to recovery rates, such as the South African government's timely intervention to announce a national lockout at the early stage of the outbreak, the availability of intensive medical care, and social distancing effects. Nevertheless, this study shows that a warm climate temperature can only help COVID-19 patients recover more quickly, thereby having huge impacts on the death and active case rates.

Population-level analysis of antibiotic use and death rates in beef feedlots over ten years in three cattle-feeding regions of the United States

2021 ◽  
pp. 1-7
Author(s):  
Stephanie C. Rutten-Ramos ◽  
Shabbir Simjee ◽  
Michelle S. Calvo-Lorenzo ◽  
Jason L. Bargen
Keyword(s):  
Death Rate ◽  
Live Weight ◽  
Population Level ◽  
Antibiotic Use ◽  
The United States ◽  
Death Rates ◽  
Cattle Feeding ◽  
The Us ◽  
Rate Ratios ◽  
Beef Feedlots

Abstract OBJECTIVE To assess antibiotic use and other factors associated with death rates in beef feedlots in 3 regions of the US over a 10-year period. SAMPLE Data for 186,297 lots (groups) of finished cattle marketed between 2010 and 2019 were obtained from a database representing feedlots in the central, high, and north plains of the US. PROCEDURES Descriptive statistics were generated. Generalized linear mixed models were used to estimate lot death rates for each region, sex (steer or heifer), and cattle origin (Mexico or the US) combination. Death rate was calculated as the (number of deaths/number of cattle placed in the lot) × 100. Lot antibiotic use (TotalActiveMG/KGOut) was calculated as the total milligrams of active antibiotics assigned to the lot per live weight (in kilograms) of cattle marketed from the lot. Rate ratios were calculated to evaluate the respective associations between lot death rate and characteristics of cattle and antibiotic use. RESULTS Mean death rate increased during the 10-year period, peaking in 2018. Mean number of days on feed also increased over time. Mean TotalActiveMG/KGOut was greatest in 2014 and 2015, lowest in 2017, and moderated in 2018 and 2019. Death rate was positively associated with the number of days on feed and had a nonlinear association with TotalActiveMG/KGOut. Feeding medicated feed articles mitigated death rate. CONCLUSIONS AND CLINICAL RELEVANCE Results suggested a balance between disease prevention and control in feedlots for cattle with various risk profiles. Additional data sources are needed to assess TotalActiveMG/KGOut across the cattle lifetime.

scholarly journals What does and does not correlate with COVID-19 death rates

2020 ◽  
Author(s):  
Christopher R. Knittel ◽  
Bora Ozaltun
Keyword(s):  
Linear Regression ◽  
Public Transportation ◽  
Death Rate ◽  
Negative Binomial ◽  
Statistical Significance ◽  
County Level ◽  
Linear Regression Models ◽  
Death Rates ◽  
Socio Economic Variables ◽  
Home Values

AbstractWe correlate county-level COVID-19 death rates with key variables using both linear regression and negative binomial mixed models, although we focus on linear regression models. We include four sets of variables: socio-economic variables, county-level health variables, modes of commuting, and climate and pollution patterns. Our analysis studies daily death rates from April 4, 2020 to May 27, 2020. We estimate correlation patterns both across states, as well as within states. For both models, we find higher shares of African American residents in the county are correlated with higher death rates. However, when we restrict ourselves to correlation patterns within a given state, the statistical significance of the correlation of death rates with the share of African Americans, while remaining positive, wanes. We find similar results for the share of elderly in the county. We find that higher amounts of commuting via public transportation, relative to telecommuting, is correlated with higher death rates. The correlation between driving into work, relative to telecommuting, and death rates is also positive across both models, but statistically significant only when we look across states and counties. We also find that a higher share of people not working, and thus not commuting either because they are elderly, children or unemployed, is correlated with higher death rates. Counties with higher home values, higher summer temperatures, and lower winter temperatures have higher death rates. Contrary to past work, we do not find a correlation between pollution and death rates. Also importantly, we do not find that death rates are correlated with obesity rates, ICU beds per capita, or poverty rates. Finally, our model that looks within states yields estimates of how a given state’s death rate compares to other states after controlling for the variables included in our model; this may be interpreted as a measure of how states are doing relative to others. We find that death rates in the Northeast are substantially higher compared to other states, even when we control for the four sets of variables above. Death rates are also statistically significantly higher in Michigan, Louisiana, Iowa, Indiana, and Colorado. California’s death rate is the lowest across all states.It is important to understand that this research, and other observational analyses like it, only identify correlations: these relationships are not necessarily causal. However, these correlations may help policy makers identify variables that may potentially be causally related to COVID-19 death rates and adopt appropriate policies after understanding the causal relationship.

scholarly journals Historical Analysis of U.S. Tornado Fatalities (1808–2017): Population, Science, and Technology

2019 ◽  
Vol 11 (2) ◽  
pp. 355-368 ◽  
Author(s):  
Ernest Agee ◽  
Lindsey Taylor
Keyword(s):  
Great Plains ◽  
Death Rate ◽  
Rate Increase ◽  
Historical Analysis ◽  
The United States ◽  
Population Increase ◽  
Historical Trends ◽  
Data Record ◽  
Population Science ◽  
Expanding Population

Abstract The record of tornado fatalities in the United States for over two centuries (1808–2017) and decadal census records have been examined to search for historical trends. Particular attention has been given to the response to population growth and expansion into the tornado-prone regions of the country. The region selected includes the Tornado Alley of the central Great Plains, the Dixie Alley in the southeastern states, and the adjoining states in the Midwest that collectively encompass a 21-state rectangular region. The data record has been divided into two subintervals, Era A (1808–1915) and Era B (1916–2017), each of which consists of three equal-length periods. Era A is characterized by a growing and westward expanding population along with a basic absence of scientific knowledge, technology, and communications (for prediction, detection, and warning). This is followed by a renaissance of discovery and advancement in Era B that contributes to saving lives. The aforementioned periods are defined by a set of notable events that help to define the respective periods. A death per population index (DPI) is used to evaluate the 21 states in each era; there is a rise of mean DPI values to a maximum of 1.50 at the end of Era A and a subsequent fall to 0.21 at the end of Era B. It is also shown for all three periods in Era B that the deadliest tornado states, in ranked order, are Arkansas, Mississippi, Alabama, and Oklahoma. Suggestions are presented for ways to continue the decreasing trend in DPI, which would imply that the death rate increase is not as fast as the rate of population increase (or would even imply a decreasing death rate).

Time-Series Analysis of Suicidal and Undetermined Deaths

1997 ◽  
Vol 85 (3_suppl) ◽  
pp. 1242-1242 ◽  
Author(s):  
David Lester
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Suicide Rate ◽  
Death Rate ◽  
Death Rates ◽  
Negatively Associated ◽  
Fair Proportion ◽  
Series Analysis ◽  
The Usa ◽  
Over Time

The suicide rate and the death rate for undetermined causes were negatively associated over time from 1968 to 1990 in the USA, suggesting that these undetermined deaths may include a fair proportion of suicides. In contrast, there was no association between suicide and undetermined death rates over the states in 1980.

Calculating Age-Standardized Death Rates Among People With HIV Comparable Across Jurisdictions and Over Time

2021 ◽  
Vol 111 (1) ◽  
pp. 121-126
Author(s):  
Qiang Xia ◽  
Ying Sun ◽  
Chitra Ramaswamy ◽  
Lucia V. Torian ◽  
Wenhui Li
Keyword(s):  
United States ◽  
New York ◽  
New York City ◽  
York City ◽  
Death Rate ◽  
Age Distribution ◽  
The United States ◽  
Local Health ◽  
Death Rates ◽  
Over Time

The Centers for Disease Control and Prevention (CDC) and local health jurisdictions have been using HIV surveillance data to monitor mortality among people with HIV in the United States with age-standardized death rates, but the principles of age standardization have not been consistently followed, making age standardization lose its purpose—comparison over time, across jurisdictions, or by other characteristics. We review the current practices of age standardization in calculating death rates among people with HIV in the United States, discuss the principles of age standardization including those specific to the HIV population whose age distribution differs markedly from that of the US 2000 standard population, make recommendations, and report age-standardized death rates among people with HIV in New York City. When we restricted the analysis population to adults aged between 18 and 84 years in New York City, the age-standardized death rate among people with HIV decreased from 20.8 per 1000 (95% confidence interval [CI] = 19.2, 22.3) in 2013 to 17.1 per 1000 (95% CI = 15.8, 18.3) in 2017, and the age-standardized death rate among people without HIV decreased from 5.8 per 1000 in 2013 to 5.5 per 1000 in 2017.

An Inquiry into the Value to be Attached to the Different Recovery Rates of Different Asylums as Tests of Efficiency

1884 ◽  
Vol 30 (130) ◽  
pp. 210-222
Author(s):  
T. A. Chapman
Keyword(s):  
Recovery Rates ◽  
Death Rates

In the “Journal of Mental Science” for April, 1883, I presented some statistics as to the recovery and death-rates of asylums, especially directed to the question of the effect of the size of the asylum upon them. In that communication I stated an opinion (p. 9) that the dominant element governing the different rates of recovery in different asylums was to be found in the different classes of cases admitted into different asylums, and expressed a hope of some day being able to make a further research in this direction. Table VII. of the tables of the Association obviously afforded the most hopeful available means of doing so, but how much could not be seen until a laborious abstract of its contents for a number of asylums over a series of years was made.

scholarly journals Mortality in Childhood with reference to Hygiene

1922 ◽  
Vol 21 (2) ◽  
pp. 126-129 ◽  
Author(s):  
John Brownlee
Keyword(s):  
Death Rate ◽  
Death Rates ◽  
Registrar General

The method in which the mortality in childhood varies from age to age is a matter of very considerable interest. With each increase of unhygienic circumstances the death-rate among infants is well known to rise and it is commonly taken as a criterion of the measure of the unheathiness of the environment. In a rough way this is quite true but it is not the only criterion, any year of life might equally well be taken. The investigation in this note is based on a tabulation mande from the data published by the Registrar-General of England for the decade 1891–1900. In order tp make the statistics as homogeneous as possible the registration districts have been grouped accroding to the infantile mortalites, intervals of ten being taken in the unit. Thus those districts with death-rates between 80 and 90 have had their populations and deaths grouped togeather, those between 90 and 100 likewise and so on.

Control over Death: The Canadian Case

1974 ◽  
Vol 5 (3) ◽  
pp. 217-221 ◽  
Author(s):  
Sanford Labovitz
Keyword(s):  
Death Rate ◽  
The Other ◽  
Death Rates ◽  
Control Study

A replication of Phillips' “death control study” (of famous Americans) was carried out on two Canadian groups-one defined as famous and the other as non famous. It is hypothesized that at least some people can exert control over their death dates and that such control is oriented toward important social dates, in this instance, their birth dates. It is expected, therefore, that death rates decrease prior to birth dates and increase after them. The results support the hypothesis with one exception: the death rate for the famous Canadians, although increasing substantially after the birth dates, did not decrease prior to them.

scholarly journals Incidence of SARs-CoV-2 (Dikos-Ntsaaigii-19) Among Navajo Nation Children

2021 ◽  
Author(s):  
Joseph Angel De Soto ◽  
Babatunde Ojo
Keyword(s):  
Infection Rate ◽  
Death Rate ◽  
Signal Transduction Pathway ◽  
The United States ◽  
Vaccination Rate ◽  
Transduction Pathway ◽  
Bureau Of Indian Affairs ◽  
Infection Rates ◽  
Navajo Nation ◽  
Death Rates

On March 17, 2020 the SARs-CoV-2 virus was first reported on the Navajo Reservation. Today, the Navajo Nation has a 147% higher infection rate and a 450% higher death rate than the national average. Despite this tragedy, a glaring question remains, what is happening among the Navajo children. The study found that Navajo children had an infection rate 220% higher than the general population and a death rate from COVID 1,400% greater than non-Navajo in the United States. This occurs even though of Navajo children having a much higher vaccination rate of 68% compared to about 25% of children Nationwide. The introduction of SARs-CoV variants such as the alpha and omicron variants did not seem to play a role in these findings. The higher infection rates suggest a genetic predisposition among the Navajo to SARs-CoV-2 via the ACE-2 receptor and signal transduction pathway while the increased death rates may also suggest inferior care provided by the Bureau of Indian Affairs Hospitals.

Sign in / Sign up

Export Citation Format

Share Document