A demographic scaling model for estimating the total number of COVID-19 infections

Background Understanding how widely COVID-19 has spread is critical information for monitoring the pandemic. The actual number of infections potentially exceeds the number of confirmed cases. Development We develop a demographic scaling model to estimate COVID-19 infections, based on minimal data requirements: COVID-19-related deaths, infection fatality rates (IFRs), and life tables. As many countries lack IFR estimates, we scale them from a reference country based on remaining lifetime to better match the context in a target population with respect to age structure, health conditions and medical services. We introduce formulas to account for bias in input data and provide a heuristic to assess whether local seroprevalence estimates are representative for the total population. Application Across 10 countries with most reported COVID-19 deaths as of 23 July 2020, the number of infections is estimated to be three [95% prediction interval: 2–8] times the number of confirmed cases. Cross-country variation is high. The estimated number of infections is 5.3 million for the USA, 1.8 million for the UK, 1.4 million for France, and 0.4 million for Peru, or more than one, six, seven and more than one times the number of confirmed cases, respectively. Our central prevalence estimates for entire countries are markedly lower than most others based on local seroprevalence studies. Conclusions The national infection estimates indicate that the pandemic is far more widespread than the numbers of confirmed cases suggest. Some local seroprevalence estimates largely deviate from their corresponding national mean and are unlikely to be representative for the total population.

Research on Covid-19 from Biophysical Perspective

In this report, we discuss the current aspect of biophysics which is an essential field to investigate the structural and related properties of SARS-CoV-2 components, possible drugs likeliness and their interactions, and mathematical as well as clinical data modeling. We have emphasized that a mathematical model generates the sigmoid logistic equation that predicts the total corona virus cases and deaths in a model country with population averaged from the most vulnerable countries, such as India or USA, where the COVID-19 cases are still spiking up and from the countries which are on the process of recovering from the current pandemic. Further, the current status of COVID-19 research has been explained to understand its impacts taking Nepal as the reference country having low-income. In particular, focus is on biophysical study on structural analysis of novel coronavirus main protease which is found to influence the radial distributions of H-bonding atom pairs when interacting with the inhibitors N3. Explorations of the variations of physical parameters are found to be important in drug selective mechanism against COVID-19 infections.

Estimate of Covid prevalence using imperfect data

The real number of people who were truly infected with SARS-CoV-2, is certainly significantly larger than the official record. Few countries have tracking and testing procedures that are sufficiently robust to discover nearly all infections. In most countries they are inadequate, hence the true extent of the pandemic is unknown. The current study proposes the estimate of the COVID-19 extent for countries with sufficiently high number of deaths and cases. The estimate is based on a simple model of mortality. This model was developed for a reference country with a large number of cases and high intensity of COVID-19 testing. The model is then applied to compute apparent mortality in the target and reference countries. The number of cases in the target country is then estimated assuming constant underlying true mortality. The estimate of cases in most countries is significantly higher than the official record. As of April 12, 2020, the global estimate is 5.2 million compared to 1.8 million in the official record. The models developed in this study are available at covid-model.net. The model ignores several factors that are known to influence mortality, such as the demographics and health condition of population, state of epidemic and sociological differences between countries. While the model is rough, it nevertheless provides a unified approach to producing a systematic global estimate of the extent of the COVID-19 epidemic and can be useful for its monitoring.

Government Responses Matter: Predicting Covid-19 cases in US using an empirical Bayesian time series framework

Since the Covid-19 outbreak, researchers have been predicting how the epidemic will evolve, especially the number in each country, through using parametric extrapolations based on the history. In reality, the epidemic progressing in a particular country depends largely on its policy responses and interventions. Since the outbreaks in some countries are earlier than United States, the prediction of US cases can benefit from incorporating the similarity in their trajectories. We propose an empirical Bayesian time series framework to predict US cases using different countries as prior reference. The resultant forecast is based on observed US data and prior information from the reference country while accounting for different population sizes. When Italy is used as prior in the prediction, which the US data resemble the most, the cases in the US will exceed 300,000 by the beginning of April unless strong measures are adopted.

Asymmetric relationship between tourist arrivals and employment

This article explores the relationship between the arrival of tourists and its impact on tourism-related employment. Considering the impact of tourist arrival on employment being asymmetric, we have analyzed the relationship using the nonlinear autoregressive distributed lag method proposed by Shin et al. The article analyzed how arrivals impact on employment taking Sri Lanka as a reference country and have used annual data of the variables obtained from the Sri Lanka Tourism Development Authority. It is found that for an increase in the tourist arrival by 1000, the tourism-related job employment rises by 83.8. On the contrary, with the decline in tourist arrival by the same number, the corresponding reduction in job employment is 29.8. The relatively lower reduction in employment with the fall of tourist arrival provides relative stability of employment to the tourism workforce and is a socially desirable outcome.

El principio de igualdad en los 30 años de historia de la mujer en las fuerzas armadas

La incorporación de la mujer en las Fuerzas Armadas españolas ha sido uno de los acontecimientos más relevantes que se han dado en la historia del país. Esto ha originado un desarrollo normativo al objeto de regular la situación del personal femenino en estas unidades ya que, hasta hace treinta años, esta profesión era realizada únicamente por hombres. La sucesión de leyes ha facilitado la incorporación de un gran número de mujeres. Todo se ha desarrollado al objeto de alcanzar una igualdad efectiva. Esto ha permitido que, España se sitúe como un país referente en la OTAN en este contexto.The integration of women in the Spanish Armed Forces has been one of the most important events that have taken place in our recent history. This has led to the legal development of the professional status of women in these units, run only by men until thirty years ago. The succession of laws has facilitated the incorporation of a large number of women. Everything has been developed in order to achieve effective equality. This has allowed Spain to be a reference country in NATO.

Results of reference pricing and reimbursement discount rate schemes of Turkey

OBJECTIVES: General Directorate of Pharmaceuticals and Pharmacy (IEGM) is responsible for setting all prices for human medicinal products. The reference pricing system is used for setting these prices. Reference countries are reviewed annually and may be subject to certain alterations. There were 5 reference countries in 2009: Spain, Italy, Germany, France and Greece. The aim of this study is to show the distribution of reference countries which were used for reference pricing.METHODS: The price list of pharmaceuticals which was published by IEGM on 15.04.2011 was used for analysis. Distribution of reference countries and prices were evaluated.RESULTS: Prices of 6,251 generic and 3,703 original products were set according to the price list. 5,283 of generics and 3,306 of originals were in the positive list for reimbursement. Reference pricing was used for 2,352 generics and 2,281 originals. Prices of the remaining were set outside of reference pricing. 32 different countries were used for reference pricing. Italy was the most popular country for reference pricing. Even if it was not a reference country, Germany was used in some of the pharmaceuticals. The average reimbursement discount rate and price were 24.43% and 249 TL, respectively. There were no colerations between price and reimbursement discount rate, or reference country and reimbursement rate.CONCLUSION: It has been shown that Italy has the highest impact on the pricing of all pharmaceuticals in Turkey. Even if it was not a reference country, Germany showed to affect pharmaceuticals more than other countries which were also not used for reference pricing. Even if reimbursement discount rates are stated by the Social Security Institution (SGK), there are different discount rates for pharmaceuticals. The analysis stated that there were correlation between price, country and discount rates. This analysis is first for the literature. Further analysis is necessary in the light of price changes and newly launched pharmaceuticals.