Peter Chew Formula for maximum positive rate based on Covid19 mutant (Preprint)

2021 ◽  
Author(s):  
Peter Chew

BACKGROUND A higher positive rate indicates that a country has more undetected covid-19 carriers. Every country needs to increase their testing to minimize the positive rate. By increasing the covid-19 test to detect more undetected covid-19 carriers and isolate them to prevent them from infecting others, thereby reducing the number of undetected covid-19 carriers in the country. Since the new covid-19 mutants usually have a higher transmission rate, the maximum positive rate must be lower to ensure that the undetected virus covid-19 carriers are low and the country is controlled OBJECTIVE Since different countries have different covid-19 mutants, different covid-19 mutants have different levels of transmission. Therefore, each country must have a specific maximum positive rate based on its country’s covid-19 mutant. So, a general formula must be created to determine the maximum positive rate for each country based on its country’s covid-19 mutant. METHODS According to criteria published by World Health Organization (WHO) in May 2020, a positive rate of less than 5% covid-19 test is one indicator that the epidemic is under control in a country and the maximum positive rate is inversely proportional to the transmission rate of the covid-19 mutant. By using inversely proportional method, we get P_max= = x/(〖20 (T〗_mutant)) , where P_max=Maximum Positive rate, T_mutant= Transmission mutation covid-19 and x = transmission rate mutant as of may 2020. RESULTS By using the Peter Chew formula to calculate the maximum positive rate of Covid-19 mutants, P_max = x/(〖20 (T〗_mutant)) , each country can calculate a more specific country maximum positive rate, based on Covid -19 Mutation detection in their country. In addition, if a country finds a new highly infectious covid-19 mutant. The World Health Organization (WHO) recommends that a covid-19 positive rate of less than 5% is not suitable for the mentioned country. For example, if a new highly infectious Covid-19 mutant is detected in some countries, it is 10 times more infectious than the Beta variant. By using Peter Chew’s formula to calculate the maximum positive rate of Covid-19 mutants, we can calculate the maximum positive rate for that particular country, which is 0.5%. CONCLUSIONS By using Peter Chew’s formula, the maximum positive rate in each country is determined based on the covid-19 mutants in each country. In addition to providing a suitable maximum positive rate for each country, it can also prevent "policy makers" in certain countries from continuing to use the wrong maximum positive rate for new mutants because they have not updated the latest information, resulting in countries continuing to maintain a high infection rate.

First Monday ◽  
2020 ◽  
Author(s):  
Shekhar Shukla

The unfortunate arrival of the COVID-19 pandemic has also brought along with it a tsunami of information that can be both authentic and important as well as non-reliable and misguiding. The World Health Organization (WHO) coins this outburst of information in this era of pandemic as an infodemic. It becomes essential for societies to consume and act on trusted information in these times of uncertainty and grief. In this article, we describe and assess the role of blockchain technology and its features to establish an environment of a trusted information ecosystem. We present an equivalence mapping of these important parameters to curb an infodemic with blockchain technology features and applications. This equivalence mapping provides a directional sense to stakeholders, decision-makers, policy-makers and investors to gauge and synthesize the potential of blockchain technology for tackling an infodemic.


2017 ◽  
Author(s):  
Najet Guefradj

This layer represents the estimated percentage of post-neonatal (1 month old to 5 years old) deaths due to diarrhoea out of the total number of post-neonatal deaths for each country in 2015. Those estimates are provided by the World Health Organization and by the Maternal and Child Epidemiology Estimation Group (MCEE-John Hopkins University). Data for neonatal and under five children are also available by clicking in a specific country. You can access the report here: http://apps.who.int/iris/bitstream/10665/43840/1/9789241596435_eng.pdf For more information and to access the raw data, visit the WHO website: http://apps.who.int/gho/data/view.main.ghe1002015-CH3?lang=en Health Youth


2017 ◽  
Author(s):  
Najet Guefradj

This layer represents the estimated percentage of post-neonatal (1 month old to 5 years old) deaths due to malaria out of the total number of post-neonatal deaths for each country in 2015. Those estimates are provided by the World Health Organization and by the Maternal and Child Epidemiology Estimation Group (MCEE-John Hopkins University). Data for neonatal and under five children are also available by clicking in a specific country. You can access the report here: http://apps.who.int/iris/bitstream/10665/43840/1/9789241596435_eng.pdf For more information and to access the raw data, visit the WHO website: http://apps.who.int/gho/data/view.main.ghe1002015-CH8?lang=en Health Quality


2006 ◽  
Vol 22 (4) ◽  
pp. 506-511 ◽  
Author(s):  
Leena Eklund

The Health Evidence Network (HEN) was established approximately 3 years ago as a service to the health policy makers in the fifty-two member states of World Health Organization (WHO) Europe. The objective of the HEN is to (i) make it easier for policy makers to access evidence-based studies in the field of health, and to (ii) provide synthesis of available evidence around specific policy issues in health.


2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
C Somerville

Abstract Claire Somerville, PhD (Gender Centre, Graduate Institute of International and Development Studies, Geneva) will present research that investigates how gender and intersectionality analysis of NCDs is integrated into different levels of health policy and programming and within country level health systems and services by the World Health Organization (WHO). The research is the first of its kind and is based on a WHO document analysis and key informant interviews with key representatives working on issues of gender and NCDs within WHO. The findings of Somerville's investigation reveal how gender and its intersections is understood and mainstreamed at all three organizational levels of the WHO (headquarters (HQ), regions, and country level offices) and what the key impediments are not only in terms of mainstreaming a more relational and intersectional understanding of gender in general, but specifically in relation to NCDs.


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