Notes

Immunodiagnosis associated with cow fascioliasis using a 28 kDa Fasciola gigantica antigen.
Among identified 261 potential survey participants, 143 responded, reaching a response rate of 54.8%. Total physical activity before and during COVID-19 lockdown period were 7809.7 (3849.7-11769.8) MET-min/week and 4135.7 (867.2-7404.1) MET-min/week; p<0.0001. While energy expenditure before and during COVID-19 lockdown period were 8189.8 (4242.1-12137.6) kcal/wk and 4221.7 (1004.6-7438.8) kcal/wk; p<0.0001.

A significant reduction in self-report physical activity and energy expenditure levels were observed among physiotherapy professionals and students during the COVID-19 lockdown period.
A significant reduction in self-report physical activity and energy expenditure levels were observed among physiotherapy professionals and students during the COVID-19 lockdown period.
The objective of the study is to investigate the effects of transmission control efforts of the Philippine Government through implementation of Enhanced Community Quarantine (ECQ) on curtailing the exponential growth of the Corona Virus (Covid-19). Also, this study provides forecast of transmission rate of Covid-19 incorporating the heterogeneous characteristics of the group of population according to age.

The heterogeneous-mixing model was used to forecast the transmission rate of Covid-19 and effect of Enhanced Community Quarantine in various Local Government Units (LGUs) in the National Capital Region (NCR), Philippines.

The result of the study revealed that the mobility of people has significant contribution to the transmission rate of Covid-19. The result of the study revealed that the mobilization of workers, who are exempted in ECQ, would greatly affect the transmission of disease to those who are in the senior citizen group. selleck chemicals The increase in the confirmed cases of Covid-19 is associated with the transmission from those workers, who are exempted from ECQ to senior citizens and the young age group. LGUs in the NCR, Philippines will experience a different pattern of peak periods ranging from the third week of April to the last week of May.

This study concluded that in order to achieve the containment of the spread of Covid-19 in the Philippines, the government should be stricter in implementation of the ECQ and incorporate the different pattern of transmission of Covid-19 in deciding whether to extend or to lift the ECQ.
This study concluded that in order to achieve the containment of the spread of Covid-19 in the Philippines, the government should be stricter in implementation of the ECQ and incorporate the different pattern of transmission of Covid-19 in deciding whether to extend or to lift the ECQ.
To investigate the psycho-social factors associated with COVID-19 and the nationwide lockdown in India.

An online survey was conducted from April 11 through April 16, 2020 in 28 states and 8 union territories (UT) of India. The potential participants were recruited using snowball sampling procedure.

A cross-sectional online survey was conducted among the people of all states in India. A spatial analysis was performed and Moran's I statistic was applied to investigate the overall clustering of locations. Fisher's exact test was used to investigate associations. GeoDa and R console were used to analyze the data. A total of


1316

responses were received.

Those worried for their family's health were likely to follow the lockdown measures





(



p


<


0.001



)



.


Significant association was observed



(


p


<

al well-being of individuals, along with physical health.
Since the onset of the COVID-19 in China, forecasting and projections of the epidemic based on epidemiological models have been in the centre stage. Researchers have used various models to predict the maximum extent of the number of cases and the time of peak. This yielded varying numbers. This paper aims to estimate the effective reproduction number (R) for COVID-19 over time using incident number of cases that are reported by the government.

Exponential Growth method to estimate basic reproduction rate R
, and Time dependent method to calculate the effective reproduction number (dynamic) were used. "R0" package in R software was used to estimate these statistics.

The basic reproduction number (R
) for India was estimated at 1.379 (95% CI 1.375, 1.384). This was 1.450 (1.441, 1.460) for Maharashtra, 1.444 (1.430, 1.460) for Gujarat, 1.297 (1.284, 1.310) for Delhi and 1.405 (1.389, 1.421) for Tamil Nadu. In India, the R at the first week from March 2-8, 2020 was 3.2. It remained around 2 units for three weeks, from March 9-29, 2020. After March 2020, it started declining and reached around 1.3 in the following week suggesting a stabilisation of the transmissibility rate.

The study estimated a baseline R
of 1.379 for India. It also showed that the R was getting stabilised from first week of April (with an average Rof 1.29), despite the increase in March. This suggested that in due course there will be a reversal of epidemic. However, these analyses should be revised periodically.
The study estimated a baseline R0 of 1.379 for India. It also showed that the R was getting stabilised from first week of April (with an average R of 1.29), despite the increase in March. This suggested that in due course there will be a reversal of epidemic. However, these analyses should be revised periodically.
Ever since the Coronavirus disease (COVID-19) outbreak emerged in China, there has been several attempts to predict the epidemic across the world with varying degrees of accuracy and reliability. This paper aims to carry out a short-term projection of new cases; forecast the maximum number of active cases for India and selected high-incidence states; and evaluate the impact of three weeks lock down period using different models.

We used Logistic growth curve model for short term prediction; SIR models to forecast the maximum number of active cases and peak time; and Time Interrupted Regression model to evaluate the impact of lockdown and other interventions.

The predicted cumulative number of cases for India was 58,912 (95% CI 57,960, 59,853) by May 08, 2020 and the observed number of cases was 59,695. The model predicts a cumulative number of 1,02,974 (95% CI 1,01,987, 1,03,904) cases by May 22, 2020. As per SIR model, the maximum number of active cases is projected to be 57,449 on May 18, 2020. The time interrupted regression model indicates a decrease of about 149 daily new cases after the lock down period, which is statistically not significant.
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