Actual Number Of Cases Research Articles

Early Information on Active Cases in Zero Rejection Efforts for COVID-19 Patients in West Java Province 2021 Using the Feedforwards Multilayer Perceptron Neural Network

West Java noted, as of August 14, 2021, 653,741 people were confirmed positive for COVID-19. On the same date, the number of active COVID-19 cases in West Java was 65,000. There is a significant increase in active cases of COVID-19 in 2021 in West Java. In the period 5 June – 17 July 2021, there was an increase in the number of active cases by 95,532. In that period, active cases increased by 484%, and the Bed Occupancy Ratio (BOR) in West Java had jumped in June 2021 with the highest number of 91.6%, this figure far exceeded the WHO recommendation of 60% before finally continuing to decline and finally in August was at 30.69%. This has an impact on the incidence of patient rejection at the COVID-19 referral hospital. Active cases talk about COVID-19 patients who need medical treatment and new cases talk about the rate of spread of COVID-19 in West Java, so these two things are very strategic to study. In this study, active cases and new case were predicted using Multilayer Perceptron (MLP). The data used in this study were sourced from the COVID-19 Task Force. The data is the number of positive cases, recovered and died of COVID-19 sufferers in 34 provinces in Indonesia in the period 2 March 2020 - 14 August 2021. The results of the study found, from the results of the evaluation using data testing the number of active cases in the last 19 weeks, namely April 10 – August 14, 2021, MLP is accurate in predicting the number of active cases for the first coming week 17 times, and the next two weeks for the second week 12 times with an absolute percentage error (APE) < 20%. As for weekly new cases, MLP has been accurate 10 times for the next one week and 9 times for the next two weeks. It is hoped that the results of this study can be useful for the government as a reference in conditioning the hospital bed capacity to deal with active cases of COVID-19 in West Java in the next two weeks so that no COVID-19 patients are rejected by the hospital because the hospital is full.

Using space-time scan statistic for studying the effects of COVID-19 in Punjab, Pakistan: a guideline for policy measures in regional agriculture.

Pakistan is included in top 50 countries which are estimated to face serious agriculture and food deficiency related challenges due to the worldwide pandemic coronavirus 2019 (COVID-19). The aim of this study was to evaluate the effects of COVID-19 on food supply chain and agriculture in Punjab, Pakistan, by using space–time scan statistic (STSS). A survey was conducted at 720 points in different districts of the province. The STSS detected “active” and emerging clusters that are current at the end of our study area—particularly, 17 clusters were formed while adding the updated case data. Software ArcGIS 10.3 was used to find relative risk (RR) values; the maximum RR value was found to be 42.19 and maximum observed cases 53,265 during June 15–July 1, 2020. It was not always necessary that if the number of active cases in Punjab increased, there should be higher relative risk for more number of districts and vice versa. Due to the highest number of cases of COVID-19 and RR values during July, mostly farmers faced many difficulties during the cultivation of cotton and rice. Mostly farmers (72%) observed increase in prices of inputs (fertilizers and pesticides) during lockdown. If the supply chain of agriculture related inputs is disturbed, farmers may find it quite difficult to access markets, which could result in a decline in production and sales of crops and livestock in study area. It is suggested that to protect the food security and to decrease the effect of the lockdown, Punjab government needs to review food policy and analyse how market forces will respond to the imbalanced storage facilities and capacity, supply and demand and price control of products. The findings of this study can also help policy-makers to formulate an effective food security and agriculture adaptation strategy.

VAKSINASI DALAM MENENTANG COVID-19: ANCAMAN KESIHATAN AWAM

COVID-19 has had a significant impact on the level of human health and economic development around the world. The Malaysian Government has implemented the Movement Control Order (MCO phase 1-4) from 18th March to 12th May 2020 and Conditional MCO (CMCO phase 5) from 13th May to 9th June 2020. While MCO 3.0 has come into force from 28th May to 7th June 2021 and continued until July 2021. The measure aims to prevent the spread of COVID-19 infection and recover the country immediately. Next, the effort against COVID-19 was continued with the National Recovery Plan Strategy which started on 10th August 2021 by setting four phases and involving the MCO phase transition plan in stages. As of 18th August 2021, the total number of COVID-19 infections in Malaysia is 1,466,512 people and a total of 13,302 deaths have been recorded from 2020. While the number of active cases is still high at 254,484 cases. The first objective of this study is to discuss the threat of COVID-19 to human health. Second, to examine the trend of COVID-19 infection, and third, to analyze the vaccination process in Malaysia. This study uses a qualitative method that is secondary data by taking data from online. The results of the study found that C0VID-19 has threatened human health resulting in infection and death in large numbers. Therefore, as a current solution like other countries around the world, the Malaysian government also took the initiative to use vaccines in combating the COVID-19 pandemic through the National Covid-19 Immunization Program. This action is in line with SDG’s third goal which is Good Health and Well-Being.

Experience in International Cooperation on Organization of Anti-Epidemic Measures by Health Care Institutions under COVID-19 Pandemic in the Republic of Uzbekistan

The results of the joint work of a panel of experts from Rospotrebnadzor and healthcare professionals of the Republic of Uzbekistan on organizing activities to counter the spread of the SARS-CoV-2 virus are described in the paper.The goal of the study was to determine the main driving forces of COVID-19 spread in the Republic of Uzbekistan and develop an action plan to reduce the incidence of coronavirus infection caused by the SARS-CoV-2 virus.Materials and methods. The organization of work in 14 health care institutions in Tashkent and Samarkand, as well as in Tashkent and Samarkand Regions, was analyzed: in 7 laboratories, 6 hospitals and 1 polyclinic. The routes for the movement of personnel, the demarcation of green and red zones, the features of disinfection and the use of personal protective equipment were studied. Attention is drawn to the diagnosis of COVID-19, the use of therapy aimed at reducing the period of virus shedding, the criteria for lifting quarantine restrictions for patients.Results and discussion. The main factors in the organization of work of institutions that contribute to the spread of COVID-19 among medical personnel and the population have been identifed: the lack of equipped gateways between the red and green zones with the accessibility of adequate disinfection, the wrong choice of personal protective equipment, monitoring of contact persons for 10 days, discharge from hospitals based on clinical improvement. The incorrect use of antiviral therapy, the lack of differentiated approaches to the selection of optimal regimens have been noted. Proposals are formulated for organizing the work of healthcare institutions, taking into account the requirements of biological safety. The introduction of targeted measures in addition to those previously adopted has led to a signifcant improvement in the epidemic situation: the total number of active cases in the Republic of Uzbekistan, despite the increase in testing volumes, decreased from 3,686 people on August 23 to 2335 on October 27. Towards December 20, 2020, 97 % of patients recovered completely. All diagnostic triage centers in the Republic of Uzbekistan are closed due to the absence of patients with COVID-19, most of the country’s medical institutions previously re-profled for patients with coronavirus infection have returned to the routine operations.

Systematic Assessment of COVID-19 Pandemic in Bangladesh: Effectiveness of Preparedness in the First Wave.

Background: To develop an effective countermeasure and determine our susceptibilities to the outbreak of COVID-19 is challenging for a densely populated developing country like Bangladesh and a systematic review of the disease on a continuous basis is necessary.Methods: Publicly available and globally acclaimed datasets (4 March 2020–30 September 2020) from IEDCR, Bangladesh, JHU, and ECDC database are used for this study. Visual exploratory data analysis is used and we fitted a polynomial model for the number of deaths. A comparison of Bangladesh scenario over different time points as well as with global perspectives is made.Results: In Bangladesh, the number of active cases had decreased, after reaching a peak, with a constant pattern of death rate at from July to the end of September, 2020. Seventy-one percent of the cases and 77% of the deceased were males. People aged between 21 and 40 years were most vulnerable to the coronavirus and most of the fatalities (51.49%) were in the 60+ population. A strong positive correlation (0.93) between the number of tests and confirmed cases and a constant incidence rate (around 21%) from June 1 to August 31, 2020 was observed. The case fatality ratio was between 1 and 2. The number of cases and the number of deaths in Bangladesh were much lower compared to other countries.Conclusions: This study will help to understand the patterns of spread and transition in Bangladesh, possible measures, effectiveness of the preparedness, implementation gaps, and their consequences to gather vital information and prevent future pandemics.

Reinfections in COVID-19 Patients: Impact of Virus Genetic Variability and Host Immunity.

The COVID-19 pandemic is still posing a devastating threat to social life and economics. Despite the modest decrease in the number of cases during September–November 2020, the number of active cases is on the rise again. This increase was associated with the emergence and spread of the new SARS-CoV-2 variants of concern (VOCs), such as the U.K. (B1.1.7), South Africa (B1.351), Brazil (P1), and Indian (B1.617.2) strains. The rapid spread of these new variants has raised concerns about the multiple waves of infections and the effectiveness of available vaccines. In this review, we discuss SARS-CoV-2 reinfection rates in previously infected and vaccinated individuals in relation to humoral responses. Overall, a limited number of reinfection cases have been reported worldwide, suggesting long protective immunity. Most reinfected patients were asymptomatic during the second episode of infection. Reinfection was attributed to several viral and/or host factors, including (i) underlying immunological comorbidities; (ii) low antibody titers due to the primary infection or vaccination; (iii) rapid decline in antibody response after infection or vaccination; and (iv) reinfection with a different SARS-CoV-2 variant/lineage. Infections after vaccination were also reported on several occasions, but mostly associated with mild or no symptoms. Overall, findings suggest that infection- and vaccine-induced immunity would protect from severe illness, with the vaccine being effective against most VOCs.

In Silico Approaches for Novel Drug Discovery Against Coronavirus by Employing the Hybrid Molecular Technique: A Review

The coronavirus disease (COVID-19) is causing havoc all around the world. The number of active cases and deaths is increasing day by day. The novel coronavirus (CoV) is the causative agent of this disease. For the time being, there is no specific antiviral agent for the cure of COVID-19. A variety of drugs are being repurposed to counteract this disease. Scientists all over the world are striving to get some ideal molecules against this pandemic. Some hybrid molecules have been designed by coupling the privileged scaffolds of known antiviral and antimalarial drugs. This review deals with the hybrid molecules that have been designed and evaluated against the known targets of CoV by in silico techniques.

Spread and Endemicity of Cholera in India: Factors Beyond the Numbers.

Cholera outbreaks currently account for 1.3 to 4.0 million cases and cause between 21 000 and 143 000 deaths worldwide. Cholera is preventable by proper sanitization and immunization; however, in many developing nations such as India, cholera disease is endemic.The surveillance system in India does not adequately capture the actual number of cases. As a result, it is important to utilize limited public health resources correctly in India and other developing counties more effectively to reach vulnerable communities. In this study, we analyze how studies make sense of cholera transmission and spread in India from 1996 to 2015. Furthermore, we analyze how a more sensitive surveillance system can contribute to cholera eradication by giving rise to outbreak preparedness.

Health care reality of selected pediatric urologic surgeries in Germany from 2006 to 2019

HintergrundDie konservative und chirurgische Behandlung von Kindern ist in der urologischen Facharztweiterbildung fest verankert und stellt eine Kernkompetenz der urologischen Versorgung dar. Berufspolitisch wird seit vielen Jahren ein zunehmender Verlust dieses Schwerpunkts befürchtet. Ziel dieser Studie ist es, reale Fallzahlen und eine mögliche Dynamik in der Verteilung kinderurologischer Eingriffe auf die Fachabteilungen für Urologie und Kinderchirurgie in Deutschland zu prüfen.Material und MethodenAls Index-Eingriffe definierten wir Operationen des Hodenhochstands, der Hypospadie und des vesikoureteralen Refluxes (VUR). Mithilfe der Software reimbursement.INFO (RI Innovation GmbH, Hürth) werteten wir die öffentlich zugänglichen Qualitätsberichtsdaten der deutschen Krankenhäuser von 2006 bis 2019 aus und wiesen sie den entsprechenden Fachrichtungen zu.ErgebnisseDie Orchidopexie erfolgt häufiger in der Urologie, wohingegen die Hypospadiekorrektur und die operative Therapie des VUR häufiger in der Kinderchirurgie durchgeführt werden. Anteilig zeigte sich für die Orchidopexie und die operative Refluxtherapie keine relevante Verschiebung zwischen urologischen und kinderchirurgischen Kliniken im Untersuchungszeitraum. Bei den Hypospadiekorrekturen nimmt der Anteil der Operationen in kinderchirurgischen Einheiten zu (p < 0,0001). In der Kinderchirurgie erfolgen 84–93 % der analysierten Eingriffe in High-volume-Abteilungen während dieser Anteil in der Urologie bei 56–73 % liegt. Insbesondere die operative Refluxtherapie in der Urologie erfolgt zu einem hohen Anteil als Gelegenheitseingriff (30 % „very low volume“).SchlussfolgerungDie Qualitätsberichtsdaten ermöglichen die Erfassung der Fallzahlen und die Analyse der Verteilung zwischen Urologie und Kinderchirurgie in Deutschland. Dabei ist für die Hypospadiekorrektur eine relevante Verschiebung in Richtung der Kinderchirurgie zu beobachten. Die Ursachen und möglichen berufspolitischen Konsequenzen dieser ersten Erhebung sind komplex und bedürfen weiterer Analysen.

Covid-19 Indoor Monitoring System with Human Identification

Abstract: Covid-19 has become the worst of all pandemics seen with over 63,549,184 active cases recorded globally as on January 16, 2021. India alone has 10,553,529 active cases till date. It has brought on a new era and new way of life-rather reality where in safety has become a must for survival. Form the statistics it is observed that the number of active cases and health rate have only increased abruptly post lockdown even after implementing the guidelines proposed by the government to tackle the problem of the hour. since fever is developed in most communicable diseases, body temperature monitoring is effective for such disease, body temperature monitoring is effective for the prevention of outbreak of such diseases. Covid-19 being one of such, temperature records of symptoms and it is checked prior to allowing a person in, In social stratum it is done by person one should hold the temperature gun at entrance, and the sensor records is often inaccurate. This method also involves two people standing close, which itself is a problem in social-distancing rule. In this paper to design and develop Covid-19 indoor safety Monitoring with human identification using iot based devices. social distancing- since we use hands-free temperature sensing method which records the accurate temperature as well as human identification. Keywords: IOT, Indoor-safety, Human Identification with high Temperature.

Balance Model of COVID-19 Epidemic Based on Percentage Growth Rate

The paper examines the possibility of using an alternative approach to predicting statistical indicators of a new COVID-19 virus type epidemic. A systematic review of models for predicting epidemics of new infections in foreign and Russian literature is presented. The accuracy of the SIR model for the spring 2020 wave of COVID-19 epidemic forecast in Russia is analyzed. As an alternative to modeling the epidemic spread using the SIR model, a new CIR discrete stochastic model is proposed based on the balance of the epidemic indicators at the current and past time points. The new model describes the dynamics of the total number of cases (C), the total number of recoveries and deaths (R), and the number of active cases (I). The system parameters are the percentage increase in the C(t) value and the characteristic of the dynamic balance of the epidemiological process, first introduced in this paper. The principle of the dynamic balance of epidemiological process assumes that any process has the property of similarity between the value of the total number of cases in the past and the value of the total number of recoveries and deaths at present. To calculate the values of the dynamic balance characteristic, an integer linear programming problem is used. In general, the dynamic characteristic of the epidemiological process is not constant. An epidemiological process the dynamic characteristic of which is not constant is called non-stationary. To construct mid-term forecasts of indicators of the epidemiological process at intervals of stationarity of the epidemiological process, a special algorithm has been developed. The question of using this algorithm on the intervals of stationarity and non-stationarity is being examined. Examples of the CIR model application for making forecasts of the considered indicators for the epidemic in Russia in May-June 2020 are given.

National Vaccination and Local Intervention Impacts on COVID-19 Cases

COVID-19, as a global pandemic, has spread across Indonesia. Jakarta, as the capital of Indonesia, is the province with the most positive cases. The government has issued various guidelines, both at the central and regional levels. Since it began in 2021, the planned new measures, called ‘Pemberlakuan Pembatasan Kegiatan Masyarakat Darurat’, or PPKM emergency public activity restrictions, began with the possibility that the number of active cases might decrease. Accordingly, global vaccinations were also carried out, as they were in Indonesia. However, the first phase prioritized frontline health workers and high-risk elderly people. This study conducted a causal impact analysis to determine the effectiveness of PPKM in Jakarta and its vaccination program against the increase in daily new cases. Based on this test, PPKM showed a significant effect on the addition of daily new cases and recovered cases. Conversely, the vaccination program only had a significant impact on recovered cases. A forecast of the COVID-19 cases was conducted and indicated that the daily new cases showed a negative trend, although it fluctuated for the next 7 days, while death and recovered cases continued to increase. Hence, it can be said that the vaccination program has still not shown its effectiveness in decreasing the number of daily new cases while PPKM is quite effective in suppressing new cases.

Estimating COVID-19 cases infected with the variant alpha (VOC 202012/01): an analysis of screening data in Tokyo, January-March 2021

BackgroundIn Japan, a part of confirmed patients’ samples have been screened for the variant of concern (VOC), including the variant alpha with N501Y mutation. The present study aimed to estimate the actual number of cases with variant alpha and reconstruct the epidemiological dynamics.MethodsThe number of cases with variant alpha out of all PCR confirmed cases was estimated, employing a hypergeometric distribution. An exponential growth model was fitted to the growth data of variant alpha cases over fourteen weeks in Tokyo.ResultsThe weekly incidence with variant alpha from 18–24 January 2021 was estimated at 4.2 (95% confidence interval (CI): 0.7, 44.0) cases. The expected incidence in early May ranged from 420–1120 cases per week, and the reproduction number of variant alpha was on the order of 1.5 even under the restriction of contact from January-March, 2021, Tokyo.ConclusionsThe variant alpha was predicted to swiftly dominate COVID-19 cases in Tokyo, and this has actually occurred by May 2021. Devising the proposed method, any country or location can interpret the virological sampling data.

Crowdsourcing Data To Visualize Potential Hotspots For Covid-19 Active Cases In Indonesia

As the COVID-19 outbreak spread worldwide, multidisciplinary researches on COVID-19 are vastly developed, not merely focusing on the medical sciences like epidemiology and virology. One of the studies that have developed is to understand the spread of the disease. This study aims to assess the contribution of crowdsourcing-based data from social media in understanding locations and the distribution patterns of COVID-19 in Indonesia. In this study, Twitter was used as the main source to retrieve location-based active cases of COVID-19 in Indonesia. We used Netlytic (www.netlytic.org) and Phyton’s script namely GetOldTweets3 to retrieve the relevant online content about COVID-19 cases including audiences’ information such as username, time of publication, and locations from January 2020 to August 2020 when COVID-19 active cases significantly increased in Indonesia. Subsequently, the accuracy of resulted data and visualization maps was assessed by comparing the results with the official data from the Ministry of Health of Indonesia. The results show that the number of active cases and locations are only promising during the early period of the disease spread on March – April 2020, while in the subsequent periods from April to August 2020, the error was continuously exaggerated. Although the accuracy of crowdsourcing data remains a challenge, we argue that crowdsourcing platforms can be a potential data source for an early assessment of the disease spread especially for countries lacking the capital and technical knowledge to build a systematic data structure to monitor the disease spread.

Change-point analysis through integer-valued autoregressive process with application to some COVID-19 data.

In this article, we consider the problem of change‐point analysis for the count time series data through an integer‐valued autoregressive process of order 1 (INAR(1)) with time‐varying covariates. These types of features we observe in many real‐life scenarios especially in the COVID‐19 data sets, where the number of active cases over time starts falling and then again increases. In order to capture those features, we use Poisson INAR(1) process with a time‐varying smoothing covariate. By using such model, we can model both the components in the active cases at time‐point t namely, (i) number of nonrecovery cases from the previous time‐point and (ii) number of new cases at time‐point t. We study some theoretical properties of the proposed model along with forecasting. Some simulation studies are performed to study the effectiveness of the proposed method. Finally, we analyze two COVID‐19 data sets and compare our proposed model with another PINAR(1) process which has time‐varying covariate but no change‐point, to demonstrate the overall performance of our proposed model.

Curing or causing? HIV/AIDS in health care system of Punjab, Pakistan.

BackgroundPakistan’s National AIDS Control Program has registered 44,000 HIV/AIDS patients to date, but the actual number of cases have been estimated to be as high as 150,000–170,000. The health care system has a very important role to play in this equation and must be reformed to improve the health care services in Pakistan, with regards to HIV/AIDS.MethodsIt was a qualitative research employing a phenomenological approach. The principal researcher visited nine public and private health care facilities and conducted 19 key informant interviews with people working for providing preventive and curative services, in addition to the observations made on the site.ResultsPakistan’s health system has a limited capacity to address the HIV spread in the country, with its current resources. There is an obvious scarcity of resources at the preventive, diagnostic and curative level. However, menace can be curtailed through measures taken at the service delivery level by checking the unsafe needles practices, unclean surgical procedures and an unregulated and untrained private health workforce which are dangerous potentials routes of transmission of the virus to the general population. Healthcare establishments carry the chances of nosocomial infections including HIV/AIDS. Poverty, illiteracy and stigma associated with the disease is compounding the overall situation.ConclusionImproved accessibility to service delivery with a greater focus on prevention would be imperative to address the threat of HIV/AIDS in Pakistan. A health systems approach would help in identifying gaps at both strategic and operational levels, and concurrently find and implement solutions.

Analysis and forecasts for trends of COVID-19 in Pakistan using Bayesian models.

BackgroundCOVID-19 is currently on full flow in Pakistan. Given the health facilities in the country, there are serious threats in the upcoming months which could be very testing for all the stakeholders. Therefore, there is a need to analyze and forecast the trends of COVID-19 in Pakistan.MethodsWe have analyzed and forecasted the patterns of this pandemic in the country, for next 30 days, using Bayesian structural time series models. The causal impacts of lifting lockdown have also been investigated using intervention analysis under Bayesian structural time series models. The forecasting accuracy of the proposed models has been compared with frequently used autoregressive integrated moving average models. The validity of the proposed model has been investigated using similar datasets from neighboring countries including Iran and India.ResultsWe observed the improved forecasting accuracy of Bayesian structural time series models as compared to frequently used autoregressive integrated moving average models. As far as the forecasts are concerned, on August 10, 2020, the country is expected to have 333,308 positive cases with 95% prediction interval [275,034–391,077]. Similarly, the number of deaths in the country is expected to reach 7,187 [5,978–8,390] and recoveries may grow to 279,602 [208,420–295,740]. The lifting of lockdown has caused an absolute increase of 98,768 confirmed cases with 95% interval [85,544–111,018], during the post-lockdown period. The positive aspect of the forecasts is that the number of active cases is expected to decrease to 63,706 [18,614–95,337], on August 10, 2020. This is the time for the concerned authorities to further restrict the active cases so that the recession of the outbreak continues in the next month.

Cumulated burden of COVID-19 in Spain from a Bayesian perspective.

BackgroundThe main goal of this work is to estimate the actual number of cases of Covid-19 in Spain in the period 01-31-2020/06-01-2020 by Autonomous Communities. Based on these estimates, this work allows us to accurately re-estimate the lethality of the disease in Spain, taking into account unreported cases.MethodsA hierarchical Bayesian model recently proposed in the literature has been adapted to model the actual number of Covid-19 cases in Spain.ResultsThe results of this work show that the real load of Covid-19 in Spain in the period considered is well above the data registered by the public health system. Specifically, the model estimates show that, cumulatively until June 1st, 2020, there were 2 425 930 cases of Covid-19 in Spain with characteristics similar to those reported (95% credibility interval: 2 148 261 2 813 864), from which were actually registered only 518 664.ConclusionsConsidering the results obtained from the second wave of the Spanish seroprevalence study, which estimates 2 350 324 cases of Covid-19 produced in Spain, in the period of time considered, it can be seen that the estimates provided by the model are quite good. This work clearly shows the key importance of having good quality data to optimize decision-making in the critical context of dealing with a pandemic.

Toward a Country-Based Prediction Model of COVID-19 Infections and Deaths Between Disease Apex and End: Evidence From Countries With Contained Numbers of COVID-19.

The complexity of COVID-19 and variations in control measures and containment efforts in different countries have caused difficulties in the prediction and modeling of the COVID-19 pandemic. We attempted to predict the scale of the latter half of the pandemic based on real data using the ratio between the early and latter halves from countries where the pandemic is largely over. We collected daily pandemic data from China, South Korea, and Switzerland and subtracted the ratio of pandemic days before and after the disease apex day of COVID-19. We obtained the ratio of pandemic data and created multiple regression models for the relationship between before and after the apex day. We then tested our models using data from the first wave of the disease from 14 countries in Europe and the US. We then tested the models using data from these countries from the entire pandemic up to March 30, 2021. Results indicate that the actual number of cases from these countries during the first wave mostly fall in the predicted ranges of liniar regression, excepting Spain and Russia. Similarly, the actual deaths in these countries mostly fall into the range of predicted data. Using the accumulated data up to the day of apex and total accumulated data up to March 30, 2021, the data of case numbers in these countries are falling into the range of predicted data, except for data from Brazil. The actual number of deaths in all the countries are at or below the predicted data. In conclusion, a linear regression model built with real data from countries or regions from early pandemics can predict pandemic scales of the countries where the pandemics occur late. Such a prediction with a high degree of accuracy provides valuable information for governments and the public.

Assessment of precautionary measures against COVID-19 in Indonesian workplaces

As the coronavirus disease 19 (COVID-19) pandemic spread across Indonesia, the precautionary measures have been taken by nearly all stakeholders, including industries and employers. The purpose of this study is to assess the measures took against COVID-19 pandemic in the workplaces across the country. This research involved participants from 103 different companies using a questionnaire adapted from Better Work Indonesia (BWI), occupational safety and health association (OSHA) and centers for disease control and prevention (CDC) COVID-19 guidelines. The data analysis conducted with descriptive statistics that resulted with the following key findings. Indonesian companies have taken precautionary measures against COVID-19 at their workplace. Most aspects of COVID-19 preventive measures: policy and procedure, operational aspect, health and safety, and external activities have been observed by the vast majority of the subjects. This study found that among 30 COVID-19 programs, the emergency exercise at work was the only one that had not been conducted by more than half of respondents. As the number of active cases still growing at the time this study conducted, all precautionary measures against COVID-19 shall be carried out with consistency by the company management).