Category Archives: Covid-19

SIOUX FALLS, S.D. (KELO) The COVID-19 death toll throughout the pandemic is at 3,021 in South Dakota.

According to Wednesdays update to the South Dakota Department of Health COVID-19 dashboard, the deaths are up four from 3,017 the previous week. The new reported deaths include two males and two females in the following age categories: 1 in 70-79 and 3 in 80+. New deaths were reported in the following counties: Brule, Day, Hand and Pennington.

Active cases are now at 540, down from the previous report (709).

As of September 28, 53 of South Dakotas 66 counties are listed as having high or substantial community spread. High community spread is 100 cases or greater per 100,000 or a 10% or greater PCR test positivity rate.

There are now 81 people hospitalized due to COVID-19, down from last week (94). Throughout the pandemic, there have been 11,768 total people who have been hospitalized.

There were 732 confirmed and probable COVID-19 cases reported.

The states total case count is now at 261,371, up from last week (260,639). That total does not include at-home positive results as those are not required to be reported to the state.

The latest seven-day PCR test positivity rate for the state is 13.8% for September 20-26.

The number of recovered cases is at 257,810.

The number of Omicron cases detected in South Dakota through sentinel monitoring is now at 1,659. The state is also reporting 164 Omicron BA.2 cases.

There have been 1,720 Delta variant cases (B.1.617.2 and AY lineages) is detected in South Dakota through sentinel monitoring. There have been 176 cases of the B.1.1.7 (Alpha variant), 4 cases of P.1. (Gamma variant) and 2 cases of the B.1.351 (Beta variant).

For COVID-19 vaccines, 77% the population 5-years-old and above has received at least one dose while 61% have completed the vaccination series. For booster doses, 34% of those eligible have completed their booster dose.

There have been 761,133 doses of the Pfizer vaccine administered, 513,911 of the Moderna vaccine and 38,368 doses of the Janssen vaccine.

There have been 1,313,439 total doses administered in South Dakota with 536,433 total persons receiving the vaccine.

Originally posted here:

COVID-19 in South Dakota: Hospitalizations, active cases down as 4 new deaths reported - KELOLAND.com

By Anchorage Daily News

Updated: 2 hours ago Published: 4 hours ago

There were 34 COVID-positive patients hospitalized in Alaska as of Wednesday, according to the state health department. Hospitalizations were down from the previous week, when 37 COVID-positive patients were reported.

Here are other highlights from this weeks updated COVID-19 data from the Alaska Department of Health:

The state health department reported no additional COVID-19 deaths among residents. There have been 1,329 COVID-19 deaths reported among Alaska residents since the beginning of the pandemic.

In Alaska, 800 new cases were reported over a seven-day period, a decrease from 1,111 cases reported last week. That data doesnt include at-home tests, which dont get reported.

Alaskas seven-day case rate per 100,000 fell to 32nd among U.S. states, according to a CDC tracker.

Statewide, 68.1% of Alaskans six months and older had received at least one dose of the COVID-19 vaccine, while 28.3% had received at least one booster shot.

[Five things about COVID we still dont understand - at our peril]

Note: The state health department said that it will no longer release a weekly COVID-19 data overview on Wednesdays, but it will continue to produce a weekly update on COVID-19 and flu that contains similar information.

Read more here:

Tracking COVID-19 in Alaska: State reports another week of declining cases and hospitalizations - Anchorage Daily News

COVID-19 is a respiratory illness, so its not surprising that exposure to poor air quality worsens patient outcomes. But how does air pollution affect people who are vaccinated?

To answer that question, a team of researchers analyzed data from more than 50,000 COVID-19 patients across Southern California. By comparing publicly available air quality monitoring data with deidentified patient medical records, they first established that regardless of air pollution exposure, vaccines go a long way in reducing COVID-19 hospitalizations.

Fully vaccinated people had almost 90% reduced risk of COVID hospitalization, and even partially vaccinated people had about 50% less risk, saidZhanghua Chen, PhD, assistant professor of population and public health sciences at the Keck School of Medicine of USC and co-first author of the study.

But air pollutantsin particular fine particles (PM2.5) and nitrogen dioxide (NO2)are still harmful. Even among people who were vaccinated, exposure to those two pollutants over the short or long term increased the risk of hospitalization up to 30%.

Among vaccinated people, the detrimental effect of air pollution exposure is a little smaller, compared to people who were not vaccinated, Chen said. But that difference is not statistically significant.

The study was just published in theAmerican Journal of Respiratory and Critical Care Medicine. The research builds on the teamsearlier findings, which helped establish the link between air pollution exposure and COVID-19 severity.

These findings are important because they show that, while COVID-19 vaccines are successful at reducing the risk of hospitalization, people who are vaccinated and exposed to polluted air are still at increased risk for worse outcomes than vaccinated people not exposed to air pollution, said corresponding author Anny Xiang, PhD, MS, a senior research scientist at Kaiser Permanente Southern Californias (KPSC) Department of Research & Evaluation.

Short-term and long-term exposures

The researchers analyzed medical records, which were deidentified to protect patient privacy, from KPSC patients. Across the health care network, 50,010 patients, ages 12 and up, were diagnosed with COVID-19 in July or August of 2021, when the Delta variant was circulating and many people had been vaccinated.

Then, the researchers calculated estimated air pollution exposure levels for each participant based on residential addresses. They looked at average PM2.5, NO2, and ozone (O3) levels during the one-month and one-year periods before each patient received a COVID-19 diagnosis.

We investigated both long-term and short-term air pollution exposure, which may influence COVID-19 severity through different mechanisms, said Chen.

Over the long term, pollution is linked to increases in cardiovascular and lung diseases, which are in turn linked to more severe COVID-19 symptoms. In the short term, air pollution exposure may worsen inflammation in the lungs and could even alter the immune response to the virus.

Chen, Xiang, and their colleagues found that among 30,912 people who were unvaccinated, high short-term PM2.5 exposure increased the risk of COVID-19 hospitalizations by 13%, while long-term exposure increased the risk by 24%. For NO2, short-term exposure raised hospitalization risk by 14% and long-term exposure raised the risk by 22%. The pollutant O3 was not significantly associated with COVID-19 hospitalizations.

For those who were partially or fully vaccinated, the hospitalization risks related to air pollution exposure were slightly lowerbut the difference was not statistically significant.

Using data from medical records and neighborhood-level databases, the researchers were able to control for the effects of vaccination status, age, sex, race/ethnicity, health insurance status, body mass index, smoking history, health comorbidities, education level, income level and population density.

Improving indoor air quality

The findings suggest that in order to reduce severe cases of COVID-19, we need to improve air quality. This spring, the Biden Administration launched theClean Air in Buildings Challenge, an effort to install high-efficiency particulate absorbing(HEPA) filters in schools and other public buildings.

Chen recently received funding to conduct clinical trials of HEPA filters to determine whether they reduce the risk of diabetes and cardiovascular disease. Her team will also continue their collaboration with KPSC to study the direct impacts of indoor air purifiers on COVID-19 patients.

About this study

In addition to Chen and Xiang, the studys other authors are Brian Z. Huang and Frank D. Gilliland of the Department of Preventive Medicine, Keck School of Medicine of USC; Margo A. Sidell, Ting Chow and Mayra P. Martinez of the Department of Research & Evaluation, Kaiser Permanente Southern California; and Fred Lurmann of Sonoma Technology, Inc.

This work was supported by the National Institute of Environmental Health Sciences at the National Institutes of Health [3R01ES029963-01] and the Keck School of Medicine of USCs Department of Preventive Medicine COVID-19 Pandemic Research Center (CPRC).

About Keck School of Medicine of USC

Founded in 1885,theKeck School of Medicine of USCis one of the nations leading medical institutions, known forinnovative patient care, scientific discovery, education and community service. Medical and graduate students work closely with world-renowned faculty and receive hands-on training in one of the nations most diverse communities. They participate in cutting-edge research as they develop into tomorrows health leaders.The Keck School faculty are key participants in training of 1200 resident physicians across 70 specialty and subspecialty programs, thus playing a major role in the education of physicians practicing in Southern California.

American Journal of Respiratory and Critical Care Medicine

Meta-analysis

People

The independent effect of COVID-19 vaccinations and air pollution exposure on risk of COVID-19 hospitalizations in Southern California

20-Sep-2022

Read the original post:

Exposure to air pollution worsens COVID-19 outcomes, even among the fully vaccinated - EurekAlert

Nows the time to get the COVID-19 booster and flu shots especially with winter approaching.

Mark Mirko

/

Connecticut Public

We hit 400 patients with COVID in the hospital about a week ago, said Dr. Manisha Juthani, Connecticuts public health commissioner.. I do expect that that number will continue to rise over the next couple of weeks.

Juthani told Connecticut Public Radios Where We Live that her department is also monitoring the flu across the state. Less mask usage this winter may result in more flu cases.

Flu has been low for the last couple of years, Juthani said. We do anticipate its going to be much higher this year; we already see activity. Were expecting a worse flu season than usual.

Still, theres good news. According to the CDC and hospital systems, with vaccines, people are protected against the severity of both the flu and COVID-19. Juthani said the new COVID bivalent booster would prevent people from getting severely sick. Connecticut has administered close to 100,000 doses since early September.

Workforce shortages

Ahead of the anticipated uptick in COVID and flu cases, Connecticut, like the rest of the U.S., is facing nursing shortages.

Healthcare workers are still doing their part that they do every single day in hospitals, Juthani said. There are people who certainly have left the workforce. There have been several state initiatives to bolster workforce development. But these types of initiatives take time.

Connecticut launched a higher education program earlier this year to build up the pipeline of nurses, funded by the American Rescue Plan Act.

Emily Caminiti contributed to this report.

See the article here:

Expect an uptick in COVID-19 and flu cases, Connecticut's public health expert warns - Connecticut Public

Introduction

The coronavirus disease 2019 (COVID-19) pandemic is a worldwide threat in many aspects, making developing countries with scarce primary health care and medical services more vulnerable. Evaluation of the relationship between the COVID-19 pandemic, sociodemographic variables, and medical services provides useful information to take countermeasures to stop the infection spread and could mitigate the damage. Therefore, this study investigated the relationship between the spread of COVID-19 and sociodemographic variables, medical services, and the transportation system in Myanmar.

This study was a cross-sectional study and was conducted using data on COVID-19 cases from August 20, 2020 to January 31, 2021 in Myanmar. We evaluated the association between the COVID-19 cases and 13 independent variables that were sociodemographic, medical services, and transportation system factors using simple linear regression analysis and multiple linear regression analysis in three phases (increasing (from August 20th to October 10th), stable (from October 11st to December 4th) and decreasing phases (from December 5th to January 31st)) on the infection timeline.

It was found that the population density wasparallelly associatedwith COVID-19 cases. On the other hand, among the medical services factors, the number of doctors was parallelly associated with COVID-19 cases and the number of nurses was inversely related to COVID-19 cases.

The result indicated that a high population density area was a risk factor for the increase of COVID-19 cases. This supported the worldwide countermeasures to deal with the spread of the infection, such as social distancing, banning largegatherings, working from home, and implementing quarantine procedures for suspected individuals to reduce person-to-person contact. Finally, at least in Myanmar, employing a large number of nurses could reduce the emergence ofnew COVID-19 cases. We believe that our study can make valuable contributions to tackling future epidemics like COVID-19 not only in Myanmar but also in other developing countries.

This article was previously presented as an abstract at the 91stconference of The Japanese Society for Hygiene (JSH ) on March 08, 2021.

The first case of the coronavirus disease 2019 (COVID-19) was reported in Wuhan, the capital city of Hubei Province of China on December 8, 2019[1]. The infection subsequently spread rapidly across the world, turning the epidemic into a pandemic. The World Health Organization (WHO) reported that by July 2022, over 564 million people were infected and suffering and of these nearly 6.4 million people died worldwide, while in Myanmar, the number of cumulative COVID-19 cases was 614,009 and deaths were 19,434 [2]. Coronavirus belongs to theCoronaviridaefamily, which consists of enveloped viruses with positive-sense single-stranded RNA. Primal clinical symptoms are high fever, cough, myalgia, and dyspnea, which could develop into acute respiratory distress syndrome or multiorgan failure[3], finally causing death. COVID-19 spreads from person to person via droplet infection [4]. Since the R naught (R0: basic reproduction number) of COVID-19 has been measured at 3.0 and above[5], it is more contagious than the influenza virus (R0 of Influenza A(H1N1) is 1.4 to 1.6) [6]. The average incubation period of the virus is between three and seven days, and over 80% of the virus may have been transmitted - asymptomatically or symptomatically - with the early onset of symptoms[7,8]. Since the vaccine had not yet been invented, during the early stages of the COVID-19 pandemic, countermeasures such as keeping social distancing, maintaining personal hygiene, wearing masks, and lockdowns of cities[9,10] were implemented.The transmission of the virus and the infection rate was restrainedby various government policies such as mitigation and containment strategies [11].

The COVID-19 pandemic has been associated with several factors like socioeconomic factors, demographic factors, climate, and individual immunity [10,12-14], but the impact of these factors has varied across countries. Therefore, it is important to detect the factors that affected the COVID-19 infection in each area. While there has been a considerable amount of literature on the topic available with regard to developed countries, the literature is scant in developing countries,and there is none pertaining to Myanmar.Medical services are now vulnerable in Myanmar. Therefore, we tried to evaluate the relation between the COVID-19 cases and some independent variables such as sociodemographic factors, medical services, and the transportation system. We believe that our findings are a valuable contribution for formulating government policies and handling further outbreaks.

The first COVID-19 case in Myanmar was reported on March 23, 2020, and the first death was confirmed on March 31, 2020[15]. Since the rise in patients started on August 20, 2020 and converged in February 2021,we used the COVID-19 data from August 20, 2020 to January 31, 2021.

Myanmaris dividedintoseven regions, seven states, and one union territory, and its total population is 51,486,253[16]. Therefore, we set the 15 survey areas as our evaluation fields.

The number of COVID-19 cases from August 20, 2020, to January 31, 2021 was retrieved from the Ministry of Health and Sport (Myanmar)[15]. Our evaluation of independent variables in this study, such as population density; aging rate (population aged 65 years and above); unemployment rate; average monthly income; average annual temperature; number of doctors, nurses, midwives, hospitals and rural health centers; number of cars, buses, and two-wheelers were derived from the Myanmar Population Census[16]and the official government websites of Myanmar (Ministry of Labor, Employment, and Social Security[17], Ministry of Transportation and Communication[18], Ministry of Health and Sports[15], Department of Meteorology and Hydrology[19], and Myanmar Statistical Information Services[20]). The population density, aging rate, and unemployment rate were of 2014[16]; the year 2017 was considered for the average income per month [21]; average annual temperature was based upon the years 2008-2017[20]; medical facility and staff data was from 2021 [15]; and transportation data was from 2020 [18].Since Myanmar is a developing country, its electronic database system is not very advance; therefore, it was very difficult to assemble independent variables data of the same year. However, we have conducted this research with limited datasets without ignoring the fact that there have been some changes in these datasets for several years.

Figure1indicates the epidemic curve of COVID-19 casesin Myanmar.The period was divided visually into three phases as shown in Figure 1 - the increasing, the stable, and the decreasing phase - and we evaluated the relationship between the COVID-19 cases and the independent variables for each phase.

Simple linear regression analysis and multiple linear regression analysis were obtained with p < 0.05 being considered statistically significant. We used the variance inflation factor (VIF) index to evaluate the degree including multicollinearity and removed some variables to reduce the VIF index (about 5.0 or less) and to fit the model. High VIF contains much multicollinearity that needs to be corrected generally [22].We evaluated the relation between the number of COVID-19 cases and the independent variables usingmultiple linear regressionanalysis. Excel 2003 (Microsoft Corporation, Redmond, USA) and JMP 16 (SAS Institute, Cary, USA) were used for the analysis.

Figure1shows the epidemic curve of COVID-19 cases in Myanmar. The number of COVID-19 cases for increasing, stable, and decreasing phases are 25668, 71983, and 42059, respectively. Table1summarizes the outline of the number of COVID-19 cases, the sociodemographic variables and other independent variables. Yangon is the biggest city in Myanmarand ranked first in population, population density, average income, number of doctors, and number of cars.

We separately evaluated the correlation between the number of COVID-19 cases(per 10,000 people) and the variables in each of the three phases by using a simple linear regression analysis (Table2) in each phase. The results indicated a parallel relationship between COVID-19 cases and population density, average income, and the number of doctors, cars, and buses.

Additionally, we verified the relationship between the number of COVID-19 casesand the variables using multiple linear regression analysis (Table3, Model 1). Thereafter, we eliminated the number of cars, buses, nurses, midwives, and hospitals from the variables to minimize VIF (about 5.0 or less) for reducing multicollinearity, and re-evaluated the relationship (Table3, Model 2). We detected a statistically significant parallel relationship between the cases and population density. However, this relationship was not observed for the decreasing phase.

After we divided the variables into two categories - the variables excluding medical services and the variables concerning medical services, we also investigated the relationship between the number of COVID-19 cases and the variables (Tables 4, 5 ) while excluding the number of cars, buses, midwives, and hospitals to minimize VIF. The results showed that the population density was statistically significantly associated with increased cases during all three phases (increasing, stable, and decreasing) (Table 4 Model 4). The number of doctors displayed a significant parallel association, while the number of nurses revealed a significant reverse association statistically (Table 5 Model 6).

The COVID-19 pandemic has caused immense suffering and many deaths worldwide. This disease has had a detrimental impact globally and affected both developed and developing countries, including Myanmar. Immunization by vaccination was limited to developed countries, and it took a long time for the vaccine to be available in developing countries. Therefore, it is important to understand the risk factors that can cause the infection to spread, and to put into place effective countermeasures.

Since the coronavirus gets transmitted from person to person through droplet infection, contact with people is a high-risk factor. Living in urban or major cities [10,23] and a crowded public transportation system [24-26]could be assumed risk factors for increasing COVID-19 cases. It was reported that there was a parallel relation between population density and virus contagion and morbidity [27,28]. Moreover, the number of buses was considered a more important factor for rapid contagion than the number of cars[24,26,29,30]. Using public transportation could increase the risk of contagion [24,26,29,30]. Other factors such as high unemployment rate [14], being senior citizens [31], and residing in areas with poor medical facilities [32,33] could be factors causing the rise of COVID-19 cases. Additionally, high income, a developing economy, and high employment rate could induce the rapid spread of emerging infectious diseases due to increased human mobility necessitated by economic activity [14,34]. Therefore, it is important to detect risk factors for the increase of COVID-19 cases, and prevent the infection when effective vaccines are not available. We evaluated the relationship between the COVID-19 cases and the variables such as sociodemographic and other factors (population density, aging rate, unemployment rate, average income per month, average annual temperature, numbers of hospitals, health centers, doctors, nurses, and transportation system (buses, cars and two-wheelers)).

Table2indicates that population density, average income per month, and the number of doctors, cars, and buses had a parallel correlation with the number of COVID-19 cases. Our results aligned with those of other studies [24-28,35,36].

We also re-evaluated the relationship using multiple linear regression analysis to evaluate the influence of the variables individually with reducing multicollinearity. We found that only population density was significantly associated with the increased number of COVID-19 cases (Table3 Model 2). It means that living in urban or major cities could be a potential risk for the infection spread. Therefore, staying at home, keeping social distance, and banning large gatherings could be effective countermeasures to contain the spread of the COVID-19 infection, especially for those living in densely populated areas. During the decreasing phase, the population density was not associated with the increase in COVID-19 cases. Though the reason is unclear, we believe that the preventive countermeasures were already effective in the decreasing phase. We could not evaluate the relation between the COVID-19 cases and the transportation system, such as the number of cars and buses, because of high multicollinearity with other variables.

Some references suggest that medical services were a mitigating factor in containing the spread of COVID-19 [33,37,38]. However, we could not evaluate this due to high multicollinearity with other variables. Therefore, we evaluated the relation between the COVID-19 cases and the variables excluding medical services and the variables concerning medical services (Tables 4, 5). Our finding was that there was a significant parallel correlation between the population density and the number of doctors with the number of COVID-19 cases, while there was an inverse correlation with the number of nurses. Some studies showed that medical services could be an important protective measure for COVID-19 infection [33,37,38]. However, the relation between the number of doctors and the number of COVID-19 cases in our study did not align with the results of other studies [33,39]. A plausible reason is that we detected a high correlation between the population density and the number of doctors. First, there are not many doctors in Myanmar, and they are concentrated in the highly populated areas; moreover, their main role is that of curative care. The infection prevention activities are mainly carried out by nurses. Previous studies have also indicated that nurses played an important role in the successful prevention and control of mosquito-borne outbreaks, such as the zika and dengue viruses [40]. The results of our study did not show a correlation between the number of nurses and the population density. Notably, there is an imbalance between doctors and nurses in Myanmar [41].

Some studies have reported that high incomes and increasing employment rates are factors responsible for the spread of emerging infectious diseases [14,34]. Additionally, elderly people are more prone to infection [31]and could be a risk factor for contagion. However, we could not find any significant association between the COVID-19 cases and the aging rate, unemployment rate, or average income in Myanmar. Though we could not provide sufficient reasons for this, the difference in the unemployment rate, average income and aging rate between areas was small (Table 1) when compared to other reports [42].

Our study is not without limitations. We acknowledge that vaccination is an important countermeasure for infectious diseases. However, since most people were not vaccinated before January 31, 2021, we could not evaluate the influence of vaccination on the spread of the infection. Moreover, Myanmar was faced with a military coup on February 1, 2021, which hindered our efforts to obtain additional detailed information on the COVID-19 contagion and vaccination status.

The formulation of governmental policies with regard to COVID-19 is an important countermeasurefor reducing infection. The countermeasures employed in Myanmar were social distancing, restricting gatherings of more than 15 people, a temporary ban on international commercial flight landings, establishing public health labs, and home quarantining, which isolated infected individuals. However, the Myanmar government was unable to systematically implement these countermeasures, and it was difficult to obtain the data regarding state- and region-wise anti-COVID-19 infection policies. Therefore, we could not evaluate the relation between the number of COVID-19 cases and the policies.

In general, using the latest data that are also of the same year is important for high validity. Myanmar is a developing country, and its electronic database is still not fully developed. Additionally, the political situation in Myanmar is currently unstable. The latest national demographic survey (census) was carried out in 2015, and the largest national survey, Myanmar Living Conditions Survey, was carried out in 2017. It is impossible to obtain the data for the same year as the timeline of COVID-19 outbreak. Therefore, this study had to be carried out with limited valuable data. Additionally, it is essential to identify the difference in the variables mediating the COVID-19 cases between urban and rural areas. However, unfortunately, we could not obtain detailed data on COVID-19 cases and variables area-wise (urban and rural).

Despite the limitations mentioned above, this research was the first report concerning the relationship between COVID-19 cases and variables, such as sociodemographics and other factors. We believe that this report could help to formulate countermeasures in Myanmar if and when confronted with an epidemic in the future.

This study was conducted to evaluate the relationship between the COVID-19 cases and the variables concerning the sociodemographic, medical, and transportation systems. We identified population density to be a contributing factor to the spread of infection and the number of nurses as a protective factor, in Myanmar. However, we could not indicate any correlation between the COVID-19 cases and aging rate, unemployment rate, and average income, unlike other previous studies. This is the first study to investigate the various factors regarding the COVID-19 contagion in Myanmar. It aims to provide useful information to control the spread of infectious diseases like COVID-19and makes valuable contributions for policy-makers to consider in times of future epidemics not only in Myanmar but also in other developing countries.

See the article here:

Socio-Demographic, Health, and Transport-Related Factors Affecting the COVID-19 Outbreak in Myanmar: A Cross-Sectional Study - Cureus

It is that time of year. In many places, there is a chill in the air, and soon there will be dazzling colors.

It is also the season when updated influenza shots become available, and this year, the new bivalent COVID-19 vaccines targeting multiple SARS-CoV-2 strains are also being considered.

Each February, the Food and Drug Administration (FDA) experts gather to predict the strains of flu most likely to be circulating in the following fall, and now freshly formulated, 2022-2023-specific, flu shots are available.

The two manufacturers of COVID-19 vaccines in the United States, Pfizer/BioNTech and Moderna, have also been busy developing a new bivalent booster vaccine designed to adapt more readily to ever-changing Omicron strains of the virus that causes COVID-19, SARS-CoV-2. Both companies have now received FDA approval for their new vaccines.

Which one, or both, should you get?

We asked three experts to answer a few questions for us about this autumns vaccines. Our experts are:

Dr. Farley: The bivalent Moderna COVID-19 vaccine is for individuals 18 years of age and older, whereas the bivalent Pfizer-BioNTech COVID-19 vaccine is for individuals 12 years of age and older.

Dr. Schaffner: The win is, youre eligible now, and so I would urge people to [get their COVID-19 booster].

Dr. Adajla: The people who would benefit most from an Omicron booster are those high-risk individuals who have never been boosted.

Dr. Adajla: If you fall into a high-risk category, you should not wait to be boosted.

Dr. Schaffner pointed out the things you should be mindful of before receiving a COVID-19 booster:

Dr. Schaffner: Now, there are some people who are thinking about this very carefully. For example, they have a trip planned sometime toward, lets say, the beginning of November or end of October, and theyre planning to get their updated COVID vaccines two weeks before they take their trip.

[Whether this makes sense,] I think that a lot depends on who you are. If youre younger and stronger, and dont have any underlying illnesses, if your vaccine is otherwise up-to-date, you could consider that.

If youre older, if youre frail with underlying illnesses, if you have diabetes, heart disease, lung disease, if you are immune-compromised in any way, I would urge you to get it now, rather than put it off because there are risks in the community. These Omicron variants are still circulating briskly across the country.

Dr. Schaffner: The answer is, as they would say in Minnesota, You bet!

And there are a couple of reasons for this. Your COVID-19 vaccine will not protect against influenza, and the reverse is also true: Influenza vaccine will not protect you against COVID-19. Theyre two separate viruses.

Influenza and we may have to remind people of this is another very serious winter respiratory virus.

It puts people in the same risk groups older frail, underlying illnesses, immunocompromised at increased risk of complications of influenza: pneumonia, hospitalization, and dying.

Dr. Adajla: Like is the case with every year, flu vaccination is also an important measure to take.

Dr. Farley: Yes, individuals should receive their annual flu vaccination this year, especially given that the formulation has changed to better match the anticipated circulating influenza viruses in the 2022-23 flu season.

All three experts agreed that there is no difference between getting one or the other vaccine first and that they are safe to receive together.

Dr. Adajla: As flu season has not really begun in the Northern Hemisphere, the [Omicron] booster is more important at this time.

Dr. Schaffner: Theres no contraindication for getting them at the same time. Some people will want to spread them out, simply because they dont want two sore arms at the same time. In fact, I was just giving a lecture and one of my colleagues was there. He said just yesterday he got them both, in one arm and one in the other.

Dr. Schaffner said he wanted to ease any concerns pregnant people may have about vaccines:

Should pregnant women receive these two vaccines? The answer is an unqualified yes. Its so recommended by the American College of Obstetricians and [Gynecologists]. Its clear from the data that both of these vaccines are safe during pregnancy.

We have data from influenza vaccine that [it] not only protects the mother, but some of those antibodies will cross the placenta and give the newborn protection during the first four to six months of its life.

He noted that this hasnt been as well-studied with COVID-19.

We would think its likely because thats been true in other circumstances. When moms are immunized with other vaccines TDAP, for example those antibodies go over into the baby. So, it is likely that is the case with COVID also.

More here:

Flu shot and Omicron COVID-19 booster: What to know about doubling up - Medical News Today

Sen. Ron Wyden (D-Ore.) on Sept. 28 blocked a resolution that would aim the national emergency declaration over COVID-19.

Wyden stepped in after Sen. Roger Marshall (R-Kan.), a doctor, introduced the resolution.

The one-page measure would terminate the national emergency declaration, which was initially declared by the Trump administration and has been extended through the present day by the Biden administration.

It is this declaration, coupled with other additional emergency powers currently invoked by the president, which this administration is using to supersize government in order to continue their reckless inflationary spending spree and enact their partisan agenda, Marshall said on the Senate floor in Washington. In fact, the White House uses these emergencies to justify their inflationary out-of-control spending, their unconstitutional vaccine and mask mandates, and to forgive student loans.

The declaration has enabled the U.S. Centers for Disease Control and Prevention to require data reporting and the Department of Health and Human Services to waive certain requirements for Medicare and Medicaid. It was cited by the Biden administration when officials announced in August that they would cancel thousands of dollars in student debt for millions of Americans.

Marshall, a member of the Senate Health Committee noted that President Joe Biden, a Democrat, recently said that the COVID-19 pandemic is over, which he said should mean the end of the emergency.

Wyden, the chairman of the Senate Finance Committee and a member of the Subcommittee on Health Care, said that ending the emergency would exacerbate doctor and nursing shortages.

Right now, there are requirements in Medicare for a lengthy process that must be completed before its possible to hire healthcare providers to serve Medicare patients, Wyden said. If the Marshall proposal goes into effect as written, Health and Human Services could not waive this complicated process to take care of patients. So that would leave our country short of health care providers when theres an acute, even more serious need for them.

I have never had a constituent at home, an Oregonian, say, Ron, what we need is more complicated processes and red tape in American health care. Usually, theyre talking to us about waiving things. So for those reasons I object, he added later.

Marshall took the floor after the objection, saying he agrees the shortages are a problem.

But the difference is, I dont think the government is the solution to the problem. I think the government has created the problem, he said.

The senator said that the solution is to remove some of the red tape, not to continue letting the administration utilize emergency powers.

Its my feeling that this emergency declaration allows the president and the White House to expand those powers, to take our constitutional rights away from us, Marshall said. I have encouraged people to take the vaccine and do all the right things. But I still think that its time to end the emergency, give us our God-given constitutional rights back.

I think that we should support ending this declaration of emergency.

Follow

Zachary Stieber covers U.S. and world news. He is based in Maryland.

Read the rest here:

Democrat Blocks Resolution to End National COVID-19 Emergency - The Epoch Times

In 2020, in response to the COVID-19 pandemic, population-wide non-pharmaceutical interventions were adopted in the European Union/European Economic Area (EU/EEA) with the aim of reducing close-contact transmission between people. This necessitated new data collections of updated contacts. As a result, the European Commission funded the longitudinal contact mixing (CoMix) extension of the POLYMOD study [1,2], which measured the number of daily contacts between participants of different age groups. The aim of CoMix was to assess how social mixing behaviour changed in the acute phase of the pandemic. The CoMix questionnaire was rapidly implemented first in the United Kingdom (UK), followed by Belgium and the Netherlands and, as a third stage, in over 20 countries in the EU/EEA, yielding unparalleled insight into how people changed their everyday lives in response to the real or perceived risk during a pandemic. For a timeline of the implementation of the CoMix questionnaire across the various countries, see Verelst et al [3].

The development and piloting of the CoMix questionnaire built on questions of the POLYMOD questionnaire as described in Mossong et al. [1], which contains an exemplary POLYMOD social contact diary as an attachment. The original CoMix questionnaire used in the UK was made publicly available as an attachment to the work of Gimma et al. [4]. For an overview of funding sources used for CoMix data collection in various countries, see Verelst et al [3]. For the CoMix data collection in the various European countries, the questionnaire was later updated to accommodate changes in vaccination and testing policies, and was translated into the national languages of all the participating countries and reviewed by local partners for language and cultural appropriateness.

In 2022, the CoMix survey was conducted again to enhance our understanding of contact mixing during the transition period beyond the acute phase of the COVID-19 pandemic. The questionnaire was further modified to accommodate booster vaccination and new types of tests, and incorporated additional feedback from social behaviour experts. The second round of CoMix covered nine countries (Austria, Belgium, Denmark, Italy, Estonia, Poland, Greece, Portugal, and Croatia).

The social contact data resulting from the survey can be accessed openly:

https://zenodo.org/communities/social_contact_data

Home

The questionnaire for the second round of CoMix (available above) can be accessed openly.

License for reuse: CC-BY-4.0.

[1] Mossong, Jol, et al. Social contacts and mixing patterns relevant to the spread of infectious diseases. PLoS Medicine 5.3 (2008): e74.

[2] Prem, Kiesha, Alex R. Cook, and Mark Jit. Projecting social contact matrices in 152 countries using contact surveys and demographic data. PLoS Computational Biology 13.9 (2017): e1005697.

[3] Verelst, Frederik, et al. SOCRATES-CoMix: a platform for timely and open-source contact mixing data during and in between COVID-19 surges and interventions in over 20 European countries. BMC Medicine 19.1 (2021): 1-7.

[4] Gimma, Amy, et al. Changes in social contacts in England during the COVID-19 pandemic between March 2020 and March 2021 as measured by the CoMix survey: A repeated cross-sectional study. PLoS Medicine 19.3 (2022): e1003907.

Excerpt from:

Social contact patterns in the EU/EEA during the COVID-19 pandemic - European Centre for Disease

WEST LAFAYETTE, Ind. An article on the timing of the new COVID-19 booster shot and the flu shot by Libby Richards, associate professor of nursing in Purdue Universitys College of Health and Human Sciences, is available on The Conversation. The article is available to be republished for free, online or in print, under a Creative Commons license.

The webpage for the article has information for republishing in the lower right column. Additional republishing information is also available.

Richards notes that there is a possibility of a difficult flu season this winter, which could set up a COVID-19 and flu twindemic. The good news, she says, is that vaccines are now available for both adults and children 12 years of age and up. She recommends that everyone get a flu shot by the end of October, even those who are not yet eligible for the COVID-19 booster shot.

Writer/Media contact: Steve Tally, steve@purdue.edu, @sciencewriter

Source: Libby Richards, 765-494-1392, earichar@purdue.edu

Link:

When should you get the new COVID-19 booster and flu shot?new article available for free republishing via The Conversation - Purdue University

The West Virginia Department of Health and Human Resources (DHHR) reports as of September 26, 2022, there are currently 1,402 active COVID-19 cases statewide. There have been 14 deaths reported since the last report, with a total of 7,396 deaths attributed to COVID-19.

DHHR has confirmed the deaths of an 87-year old female from Raleigh County, a 78-year old male from Kanawha County, a 94-year old female from Kanawha County, a 91-year old female from Cabell County, an 81-year old male from Logan County, a 92-year old female from Raleigh County, an 83-year old female from Jackson County, a 54-year old male from Kanawha County, a 70-year old male from Kanawha County, a 94-year old female from Cabell County, a 96-year old male from Marion County, an 84-year old female from Pocahontas County, an 83-year old female from McDowell County, and a 94-year old female from Jackson County.

COVID-19 has affected far too many West Virginians, said Bill J. Crouch, DHHR Cabinet Secretary. I urge you to utilize the vaccine calculator to help determine when you should receive your COVID-19 vaccine and Omicron booster.

CURRENT ACTIVE CASES PER COUNTY: Barbour (8), Berkeley (79), Boone (23), Braxton (6), Brooke (11), Cabell (52), Calhoun (1), Clay (5), Doddridge (2), Fayette (37), Gilmer (1), Grant (10), Greenbrier (25), Hampshire (13), Hancock (15), Hardy (17), Harrison (70), Jackson (12), Jefferson (57), Kanawha (117), Lewis (4), Lincoln (11), Logan (35), Marion (45), Marshall (18), Mason (23), McDowell (21), Mercer (102), Mineral (19), Mingo (19), Monongalia (61), Monroe (11), Morgan (13), Nicholas (24), Ohio (32), Pendleton (5), Pleasants (13), Pocahontas (6), Preston (29), Putnam (36), Raleigh (68), Randolph (20), Ritchie (4), Roane (11), Summers (7), Taylor (26), Tucker (5), Tyler (1), Upshur (23), Wayne (24), Webster (6), Wetzel (11), Wirt (2), Wood (54), Wyoming (52). To find the cumulative cases per county, please visit coronavirus.wv.gov and look on the Cumulative Summary tab which is sortable by county.

West Virginians ages 6 months and older are eligible for COVID-19 vaccination. All individuals ages 6 months and older should receive a primary series of vaccination, the initial set of shots that teaches the body to recognize and fight the virus that causes COVID-19. Those ages 5-11 years are recommended to get an original (monovalent) booster shot when due, and those ages 12 years and older are recommended to get an Omicron booster shot (bivalent) at least two months after completing their primary series.

Visit the WV COVID-19 Vaccination Due Date Calculator, a free, online tool that helps individuals figure out when they may be due for a COVID-19 shot, making it easier to stay up-to-date on COVID-19 vaccination. To learn more about COVID-19 vaccines, or to find a vaccine, visit vaccines.gov, vaccinate.wv.gov, or call 1-833-734-0965. Please visit the COVID-19 testing locations page to locate COVID-19 testing near you.

Read this article:

COVID-19 Daily Update 9-26-2022 - West Virginia Department of Health and Human Resources