Pertussis epidemiology in Argentina: TRENDS after the introduction of maternal immunisation

AbstractData on the impact of the recently recommended maternal pertussis vaccination are promising, but still insufficient to universalise this approach. We thus compared the epidemiological data prior to the implementation of this vaccination strategy in Argentina (2012) with the figures reported after 2012. During that 2010–2016 period, two outbreaks occurred, one in 2011 and another in 2016. In the former, the incidence was 6.9/100 000 inhabitants and the case-fatality rate 2.6%. Thereafter, a decline in incidence was detected until 2014. During 2015 and 2016 an increase in the incidence transpired, but this rise was fortunately not accompanied by one in the case fatality ratio. Indeed, in 2016 the case fatality ratio was the lowest (0.6%). Moreover, during the 2016 outbreak, the incidence (3.9/100 000 inhabitants) and the case severity detected in the most vulnerable population (infants 0–2 months) were both lower than those in 2011. Consistent with this pattern, in 2016, in the most populated province of Argentina (Buenos Aires), the case percentage with laboratory-positive results indicating a high number of symptoms (59.1% of the total cases) diminished compared with that detected in the 2011 outbreak without maternal immunisation (71.9%). Using the mathematical model of pertussis transmission we previously designed, we assessed the effect of vaccination during pregnancy on infant incidence. From comparisons between the epidemiological data made through calculations, emerged the possibility that vaccinating women during pregnancy would benefit the infants beyond age 2 months, specifically in the 2–12-month cohort.

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Healthcare under pressure: modelling COVID-19 fatalities with multiscale geographically weighted regressions

Kybernetes ◽

10.1108/k-07-2021-0548 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Zizi Goschin ◽

Gina Cristina Dimian

Keyword(s):

Local Level ◽

Age Distribution ◽

Case Fatality ◽

Healthcare Services ◽

Healthcare Systems ◽

Content Type ◽

Case Fatality Ratio ◽

Factors Of Influence ◽

The Impact ◽

Local Healthcare

PurposeThe paper aims to disentangle the factors behind territorial disparities in the coronavirus disease 2019 (COVID-19) case fatality ratio, focusing on the pressure put by the pandemic on healthcare services and adopting a spatial perspective.Design/methodology/approachMultiscale geographically weighted regression (MGWR) models have been used for uncovering the spatial variability in the impact of healthcare services on COVID-19 case fatality ratio, allowing authors to better capture the real spatial patterns at local level. The authors proved that this approach yields better results, and the MGWR model outperforms traditional regression methods. The selected case studies are two of the biggest UE countries, among the first affected by a high incidence of COVID-19 cases, namely Italy and Germany.FindingsThe authors found sizeable regional differences in COVID-19 mortality rates within each of the analysed countries, and the stress borne by local healthcare systems seems to be the most powerful factor in explaining them. In line with other studies, the authors found additional factors of influence, such as age distribution, gender ratio, population density and regional development.Originality/valueThis research clearly indicated that COVID-19 related deaths are strongly associated with the degree of resilience of the local healthcare systems. The authors supply localized results on the factors of influence, useful for assisting the decision-makers in prioritizing limited healthcare resources. The authors provide a scientific argument in favour of the decentralization of the pandemic management towards local authorities not neglecting, however, the necessary regional or national coordination.

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The severe acute respiratory syndrome epidemic in mainland China dissected

Infectious Disease Reports ◽

10.4081/idr.2011.1794 ◽

2011 ◽

Vol 3 (1) ◽

pp. 2 ◽

Cited By ~ 2

Author(s):

Wuchun Cao ◽

Sake J. De Vlas ◽

Jan H. Richardus

Keyword(s):

Severe Acute Respiratory Syndrome ◽

Mainland China ◽

Emerging Infectious Diseases ◽

Case Fatality ◽

Epidemiological Data ◽

Control Measures ◽

Political Commitment ◽

Younger Age ◽

Surrounding Areas ◽

The Impact

This paper provides a review of a recently published series of studies that give a detailed and comprehensive documentation of the severe acute respiratory syndrome (SARS) epidemic in mainland China, which severely struck the country in the spring of 2003. The epidemic spanned a large geographical extent but clustered in two areas: first in Guangdong Province, and about 3 months later in Beijing with its surrounding areas. Reanalysis of all available epidemiological data resulted in a total of 5327 probable cases of SARS, of whom 343 died. The resulting case fatality ratio (CFR) of 6.4% was less than half of that in other SARS-affected countries or areas, and this difference could only partly be explained by younger age of patients and higher number of community acquired infections. Analysis of the impact of interventions demonstrated that strong political commitment and a centrally coordinated response was the most important factor to control SARS in mainland China, whereas the most stringent control measures were all initiated when the epidemic was already dying down. The long-term economic consequence of the epidemic was limited, much consumption was merely postponed, but for Beijing irrecoverable losses to the tourist sector were considerable. An important finding from a cohort study was that many former SARS patients currently suffer from avascular osteonecrosis, as a consequence of the treatment with corticosteroids during their infection. The SARS epidemic provided valuable information and lessons relevant in controlling outbreaks of newly emerging infectious diseases, and has led to fundamental reforms of the Chinese health system. In particular, a comprehensive nation-wide internet-based disease reporting system was established.

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INDIA'S PRAGMATIC VACCINATION STRATEGY AGAINST COVID-19: A MATHEMATICAL MODELLING BASED ANALYSIS

10.1101/2021.05.07.21256742 ◽

2021 ◽

Author(s):

Sandip Mandal ◽

Nimalan Arinaminpathy ◽

Balram Bhargava ◽

Samiran Panda

Keyword(s):

Mathematical Modelling ◽

Health Care Professionals ◽

Rural Areas ◽

Demographic Data ◽

Case Fatality ◽

Vaccination Strategy ◽

Domain Model ◽

Vaccine Strategy ◽

Cumulative Mortality ◽

The Impact

Objectives To investigate the impact of targeted vaccination strategies on morbidity and mortality due to COVID-19, as well as on the incidence of SARS-CoV-2, in India. Design Mathematical modelling. Settings Indian epidemic of COVID-19 and vulnerable population. Data sources Country specific and age-segregated pattern of social contact, case fatality rate and demographic data obtained from peer-reviewed literature and public domain. Model An age-structured dynamical model describing SARS-CoV-2 transmission in India incorporating uncertainty in natural history parameters was constructed. Interventions Comparison of different vaccine strategies by targeting priority groups such as key workers including health care professionals, individuals with comorbidities (24 - 60 year), and all above 60. Main outcome measures Incidence reduction and averted deaths in different scenarios, assuming that the current restrictions are fully lifted as vaccination is implemented. Results The priority groups together account for about 18% of India's population. An infection preventing vaccine with 60% efficacy covering all these groups would reduce peak symptomatic incidence by 20.6% (95% uncertainty intervals (CrI) 16.7 - 25.4), and cumulative mortality by 29.7% (95% CrI 25.8- 33.8). A similar vaccine with ability to prevent symptoms (but not infection) will reduce peak incidence of symptomatic cases by 10.4% (95% CrI 8.4 - 13.0), and cumulative mortality by 32.9% (95% CrI 28.6 - 37.3). In the event of insufficient vaccine supply to cover all priority groups, model projections suggest that after keyworkers, vaccine strategy should prioritise all who are > 60, and subsequently individuals with comorbidities. In settings with weakest transmission, such as sparsely-populated rural areas, those with comorbidities should be prioritised after keyworkers. Conclusions An appropriately targeted vaccination strategy would witness substantial mitigation of impact of COVID-19 in a country like India with wide heterogenity. 'Smart vaccination', based on public health considerations, rather than mass vaccination, appears prudent.

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Data-Based Analysis, Modelling and Forecasting of the COVID-19 outbreak

10.1101/2020.02.11.20022186 ◽

2020 ◽

Cited By ~ 40

Author(s):

Cleo Anastassopoulou ◽

Lucia Russo ◽

Athanasios Tsakris ◽

Constantinos Siettos

Keyword(s):

Lower Bound ◽

Total Population ◽

Case Fatality ◽

Epidemiological Data ◽

Control Measures ◽

Suspected Case ◽

Cumulative Number ◽

Case Fatality Ratio ◽

Average Value ◽

Reported Data

AbstractSince the first suspected case of coronavirus disease-2019 (COVID-19) on December 1st, 2019, in Wuhan, Hubei Province, China, a total of 40,235 confirmed cases and 909 deaths have been reported in China up to February 10, 2020, evoking fear locally and internationally. Here, based on the publicly available epidemiological data for Hubei, China from January 11 to February 10, 2020, we provide estimates of the main epidemiological parameters. In particular, we provide an estimation of the case fatality and case recovery ratios, along with their 90% confidence intervals as the outbreak evolves. On the basis of a Susceptible-Infected-Recovered-Dead (SIDR) model, we provide estimations of the basic reproduction number (R0), and the per day infection mortality and recovery rates. By calibrating the parameters of the SIRD model to the reported data, we also attempt to forecast the evolution of the of the outbreak at the epicenter three weeks ahead, i.e. until February 29. As the number of infected individuals, especially of those with asymptomatic or mild courses, is suspected to be much higher than the official numbers, which can be considered only as a subset of the actual numbers of infected and recovered cases in the total population, we have repeated the calculations under a second scenario that considers twenty times the number of confirmed infected cases and forty times the number of recovered, leaving the number of deaths unchanged. Based on the reported data, the expected value of R0 as computed considering the period from the 11th of January until the 18th of January, using the official counts of confirmed cases was found to be ∼4.6, while the one computed under the second scenario was found to be ∼3.2. Thus, based on the SIRD simulations, the estimated average value of R0 was found to be ∼ 2.6 based on confirmed cases and2 based on the second scenario. Our forecasting flashes a note of caution for the presently unfolding outbreak in China. Based on the official counts for confirmed cases, the simulations suggest that the cumulative number of infected could reach 180,000 (with lower bound of 45,000) by February 29. Regarding the number of deaths, simulations forecast that on the basis of the up to the 10th of February reported data, the death toll might exceed 2,700 (as a lower bound) by February 29. Our analysis further reveals a significant decline of the case fatality ratio from January 26 to which various factors may have contributed, such as the severe control measures taken in Hubei, China (e.g. quarantine and hospitalization of infected individuals), but mainly because of the fact that the actual cumulative numbers of infected and recovered cases in the population most likely are much higher than the reported ones. Thus, in a scenario where we have taken twenty times the confirmed number of infected and forty times the confirmed number of recovered cases, the case fatality ratio is around ∼ 0.15% in the total population. Importantly, based on this scenario, simulations suggest a slow down of the outbreak in Hubei at the end of February.

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Connecting BCG Vaccination and COVID-19: Additional Data

10.1101/2020.04.07.20053272 ◽

2020 ◽

Cited By ~ 20

Author(s):

Devi Dayal ◽

Saniya Gupta

Keyword(s):

Disease Burden ◽

Additional Data ◽

Severe Disease ◽

Case Fatality ◽

Epidemiological Data ◽

Vaccination Policy ◽

Bcg Vaccination ◽

Significant Difference ◽

The Impact ◽

High Disease Burden

AbstractThe reasons for a wide variation in severity of coronavirus disease 2019 (COVID-19) across the affected countries of the world are not known. Two recent studies have suggested a link between the BCG vaccination policy and the morbidity and mortality due to COVID-19. In the present study we compared the impact of COVID-19 in terms of case fatality rates (CFR) between countries with high disease burden and those with BCG revaccination policies presuming that revaccination practices would have provided added protection to the population against severe COVID-19. We found a significant difference in the CFR between the two groups of countries. Our data further supports the view that universal BCG vaccination has a protective effect on the course of COVID-19 probably preventing progression to severe disease and death. Clinical trials of BCG vaccine are urgently needed to establish its beneficial role in COVID-19 as suggested by the epidemiological data, especially in countries without a universal BCG vaccination policy.

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Accounting for underreporting in mathematical modelling of transmission and control of COVID-19 in Iran

10.1101/2020.05.02.20087270 ◽

2020 ◽

Cited By ~ 1

Author(s):

Meead Saberi ◽

Homayoun Hamedmoghadam ◽

Kaveh Madani ◽

Helen M. Dolk ◽

Andrei S. Morgan ◽

...

Keyword(s):

Reproduction Number ◽

Estimation Method ◽

Case Fatality ◽

Transmission Model ◽

School Closures ◽

The Public ◽

Case Fatality Ratio ◽

And Control ◽

The Impact ◽

Pharmaceutical Interventions

SUMMARYBackgroundIran has been the hardest hit country by the outbreak of SARS-CoV-2 in the Middle East with 74,877 confirmed cases and 4,683 deaths as of 15 April 2020. With a relatively high case fatality ratio and limited testing capacity, the number of confirmed cases reported is suspected to suffer from significant under-reporting. Therefore, understanding the transmission dynamics of COVID-19 and assessing the effectiveness of the interventions that have taken place in Iran while accounting for the uncertain level of underreporting is of critical importance. We use a mathematical epidemic model utilizing official confirmed data and estimates of underreporting to understand how transmission in Iran has been changing between February and April 2020.MethodsWe developed a compartmental transmission model to estimate the effective reproduction number and its fluctuations since the beginning of the outbreak in Iran. We associate the variations in the effective reproduction number with a timeline of interventions and national events. The estimation method also accounts for the underreporting due to low case ascertainment by estimating the percentage of symptomatic cases using delay-adjusted case fatality ratio based on the distribution of the delay from hospitalization-to-death.FindingsOur estimates of the effective reproduction number ranged from 0.66 to 1.73 between February and April 2020, with a median of 1.16. We estimate a reduction in the effective reproduction number during this period, from 1.73 (95% CI 1.60 – 1.87) on 1 March 2020 to 0.69 (95% CI 0.68-0.70) on 15 April 2020, due to various non-pharmaceutical interventions including school closures, a ban on public gatherings including sports and religious events, and full or partial closure of non-essential businesses. Based on these estimates and given that a near complete containment is no longer feasible, it is likely that the outbreak may continue until the end of the 2020 if the current level of physical distancing and interventions continue and no effective vaccination or therapeutic are developed and made widely available.InterpretationThe series of non-pharmaceutical interventions and the public compliance that took place in Iran are found to be effective in slowing down the speed of the spread of COVID-19 within the studied time period. However, we argue that if the impact of underreporting is overlooked, the estimated transmission and control dynamics could mislead the public health decisions, policy makers, and general public especially in the earlier stages of the outbreak.FundingNil.

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Modelling and Analysis of 2019-nCov Epidemic in India : A study on Attack & Recovery Rate, Basic & Effective Reproductive Number, Herd Immunity Threshold & Case Fatality Ratio of Coronavirus Covid-19 in India.

10.35543/osf.io/cwyeu ◽

2020 ◽

Cited By ~ 2

Author(s):

Tanishque Propkar Malik

Keyword(s):

Herd Immunity ◽

Case Fatality ◽

Sir Model ◽

Basic Reproductive Number ◽

Reproductive Number ◽

Case Fatality Ratio ◽

Stochastic Sir ◽

Novel Coronavirus ◽

Stochastic Sir Model ◽

The Impact

Mathematical modelling of any epidemic plays a crucial role in quantifying the impact of such pathogens. This paper focuses on building a Stochastic SIR Model with non-linear parameters (to account for the effect of lockdowns) to gain a broader cognition of the 2019 novel Coronavirus pathogen (2019-nCov), widely known as Covid-19, in India. Such models help in gauging the virulence and fecundity of pathogens. Based on early transmission dynamics the basic reproductive number (R0) is computed to be 1.605. Whereas, effective reproductive number (Rt) is computed to be 4.880 as on 19 March, 2.756 as on 19 April, and 1.995 as on 19 May. Furthermore, the proportion of population that needs to be immunized (through inoculation, recovery, or death) to halt the infection spread is estimated to be 37.69%, ergo, the Herd Immunity Threshold is estimated to be 51.36 crores recoveries, if the Rt remains below 2. Rt is expected to fall below 2, and the Case Fatality Ratio (CFR) to fall to 2.14%, circa early-September (assuming minimal or no medical breakthroughs). The formulated model also provides inferential evidence manifesting the extent to which lockdowns contained the spread of the virus.

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The impact of the global distribution of bats on mortality in COVID-19 patients

Microbiology Independent Research journal ◽

10.18527/2500-2236-2020-7-1-42-48 ◽

2020 ◽

Vol 7 (1) ◽

pp. 42-48

Author(s):

Andrej Egorov ◽

◽

Julia Romanova ◽

Keyword(s):

Neutralizing Antibodies ◽

Viral Infections ◽

Fatal Outcome ◽

Case Fatality ◽

Epidemiological Data ◽

Significant Heterogeneity ◽

Large Reservoir ◽

Inflammatory Reactions ◽

The World ◽

The Impact

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated in November 2019 in China and quickly spread throughout the world causing a disease named COVID-19. An analysis of the epidemiological data on morbidity and mortality caused by SARS-CoV-2 shows that, in some countries, namely Belgium, UK, France, Italy, the Netherlands, and Spain, an increased case fatality rate (CFR) was noticed compared to the rest of the world. The CFR, calculated as the number of deaths from the total number of the cases, ranges in these countries from 10.22% to 15.8% according to the Center for Evidence-Based Medicine (CEBM). At the same time, in the countries of Central and Northern Europe, this parameter varies between 3.78% and 4.94%. This significant heterogeneity in CFR between countries has not been given a convincing explanation yet. It was found that the precursor of SARS-CoV-2 is a virus circulating in bats in China. The mutations that occurred in this virus altered its receptor specificity, thereby enabling viral infection in humans. Bats are highly resistant to viral infections due to their robust interferon system and a reduced level of inflammatory reactions. Viruses replicate in these animals up to high titers without any substantial harm to their health. As a result, bats represent a large reservoir of viruses with the potential to infect other animals, including humans. The infection of people with bat (or human) betacoronaviruses can lead to the formation of memory B-cells that provide an accelerated antibody response to cross-reactive epitopes upon subsequent infection. The early emergence of neutralizing antibodies in SARS-CoV-2 patients correlates with the severity of the disease and the likelihood of a fatal outcome. The antibody-dependent enhancement (ADE) of infection/disease known for various viruses, including SARS-CoV-1 and MERS-CoV, may be a possible cause of this phenomenon. In this article, we suggest a close connection between the distribution areas of bats carrying SARS-CoV-1-like viruses and the CFR from COVID-19.

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COVID-19-Associated Case Fatality Rate in Subjects Under 18 Years Old in Mexico, up to December 31, 2020

Frontiers in Pediatrics ◽

10.3389/fped.2021.696425 ◽

2021 ◽

Vol 9 ◽

Author(s):

Efraín Navarro-Olivos ◽

Nicolás Padilla-Raygoza ◽

Gilberto Flores-Vargas ◽

María de Jesús Gallardo-Luna ◽

Ma Guadalupe León-Verdín ◽

...

Keyword(s):

Case Fatality ◽

Viral Disease ◽

The Other ◽

Epidemiological Surveillance ◽

Age Group ◽

Cross Sectional ◽

Health Crisis ◽

Logistic Regression Models ◽

Case Fatality Ratio ◽

The Impact

Background: The emergence of the SARS-CoV-2 and the COVID-19 have become a global health crisis. The infection has been present in all the social sectors. Subjects under 18 years are one of them. The objective was to analyze the case fatality ratio of COVID-19 cases in the Mexican population under 18 years of age registered in the National Epidemiological Surveillance System from March 2020 to December 31, 2020.Material and Methods: The design is cross-sectional, quantitative, and analytical. All the suspected cases of respiratory viral disease, with a real-time polymerase chain reaction (RT-PCR) test result, aged from 0 to 17 years, were included. Descriptive statistics are presented for all the variables. Epidemiological curves were designed. The chi-squared test and its P-values were obtained to show the relationship between comorbidities and death. The case fatality ratio was computed for each comorbidity, sex, and age group. Multivariable logistic regression models were fitted to study the effect between comorbidities with the fatality of cases, adjusting for sex and age group as potential confounders. The alpha value was fixed to 0.05 to assess significance.Results: The number of records for this study was 167,856. Among them, 48,505 were from SARS-CoV-2-positive patients (28.90%), and 119,351 (71.10%) were negative. Of those who died, males (55.29%) (P < 0.05) and those under 2 years of age (50.35%) (P < 0.05) predominated. Unlike in older populations, from the comorbidities considered risk factors for death by COVID-19, only immunosuppression showed a statistically significant effect on the fatality of cases after adjustment by the other related variables. Sex and age group were not confounders for the models in those under 18 years old. Pneumonia, being younger than 5 years, and immunosuppression are related to death.Conclusion: The case fatality ratio in those under 18 years old is low. Special attention must be paid to those children under 5 years. The development of pneumonia is a warning indicator while treating them. On the other hand, having an open database of cases allows the researchers to analyze the impact of COVID-19 in different population sectors, which has clear benefits for public health.

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The Effect of Internal Corporate Social Responsibility on Job Satisfaction: An Empirical Study on Jordanian Pharmaceutical Companies

Journal of Business & Management (COES&RJ-JBM) ◽

10.25255/2306.8043.2020.8.2.112.138 ◽

2020 ◽

Vol 8 (2) ◽

pp. 112

Author(s):

Sura Altheeb ◽

Kholoud Sudqi Al-Louzi

Keyword(s):

Job Satisfaction ◽

Corporate Social Responsibility ◽

Social Responsibility ◽

Quantitative Research ◽

Skills Development ◽

Future Research ◽

Pharmaceutical Companies ◽

Corporate Social ◽

The Impact ◽

Positive Results

The current research investigates the impact of internal corporate social responsibility on job satisfaction in Jordanian pharmaceutical companies. Quantitative research design and regression analysis were applied on a total of 302 valid returns that were obtained in a questionnaire based survey from 14 pharmaceutical companies among employees, supervisors and managers. The results showed that internal corporate social responsibility was significantly related to job satisfaction and three of its dimensions, namely working conditions, work life balance and empowerment contributed significantly to job satisfaction, whereas employment stability and skills development had no contribution. This study implies that Jordanian pharmaceutical companies have to try their best to promote and facilitate internal corporate social responsibility among their employees in an effort to improve their job satisfaction, which will eventually yield positive results for the company as a whole. In light of these results, the research presented many recommendations for future research; the most important ones were the application of this study in other sectors, cultures, and countries, and using of multi method for collecting data.

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