Number Of Daily Infections Research Articles

Descripción de la Pandemia por COVID-19 en las Parroquias Samborondón, Daule y Durán

In Ecuador, the highest number of daily infections due to SARS-CoV-2 occurred in Guayaquil between April 4th and May 3th. The objective of this study is to perform a descriptive analysis of the quantitative PCR tests in real-time in Samborondón, Daule, and Durán during the months of April to August in the UEESBiolab laboratory. The results according to gender indicated that men register a greater number of positive cases compared to the female gender. People with an age within the Economically Active Population (EAP) were the ones who attended the test the most and who were positive in 13.9%. Additionally, for positive results, it was found that there is no statistically significant difference between groups for variables gender, age, canton, and parish. Finally, an increase in positive patients is observed in rural areas during this first wave of infection, with the rural population of Samborondón with the highest number of infections.

Phenomenological Modelling of COVID-19 Epidemics in Sri Lanka, Italy, the United States, and Hebei Province of China.

The COVID-19 pandemic has resulted in increasing number of infections and deaths every day. Lack of specialized treatments for the disease demands preventive measures based on statistical/mathematical models. The analysis of epidemiological curve fitting, on number of daily infections across affected countries, provides useful insights on the characteristics of the epidemic. A variety of phenomenological models are available to capture the dynamics of disease spread and growth. The number of daily new infections and cumulative number of infections in COVID-19 over four selected countries, namely, Sri Lanka, Italy, the United States, and Hebei province of China, from the first day of appearance of cases to 2nd July 2020 were used in the study. Gompertz, logistic, Weibull, and exponential growth curves were fitted on the cumulative number of infections across countries. AIC, BIC, RMSE, and R2 were used to determine the best fitting curve for each country. Results revealed that the most appropriate growth curves for Sri Lanka, Italy, the United States, and China (Hebei) are the logistic, Gompertz, Weibull, and Gompertz curves, respectively. Country-wise, overall growth rate, final epidemic size, and short-term forecasts were evaluated using the selected model. Daily log incidences in each country were regressed before and after the identified peak time of the respective outbreak of epidemic. Hence, doubling time/halving time together with daily growth rates and predictions was estimated. Findings and relevant interpretations demonstrate that the outbreak seems to be extinct in Hebei, China, whereas further transmissions are possible in the United States. In Italy and Sri Lanka, current outbreaks transmit in a decreasing rate.

Wuhan's experience in curbing the spread of coronavirus disease (COVID-19)

BackgroundSince December 2019, coronavirus disease (COVID-19) has affected over 50 000 people in Wuhan, China. However, the number of daily infection cases, hospitalization rate, lag time from onset to diagnosis date and their associations with measures introduced to slow down the spread of COVID-19 have not been fully explored.MethodsThis study recruited 6872 COVID-19 patients in the Wuchang district, Wuhan. All of the patients had an onset date from 21 December 2019 to 23 February 2020. The overall and weekly hospitalization rate and lag time from onset to diagnosis date were calculated. The number of daily infections was estimated by the back-projection method based on the number of daily onset cases. Their association with major government reactions and measures was analyzed narratively.ResultsThe overall hospitalization rate was 45.9% (95% CI 44.7 to 47.1%) and the mean lag time from onset to diagnosis was 11.1±7.4 d. The estimated infection curve was constructed for the period from 14 December 2019 to 23 February 2020. Raising public awareness regarding self-protecting and social distancing, as well as the provision of timely testing and inpatient services, were coincident with the decline in the daily number of infections.ConclusionEarly public awareness, early identification and early quarantine, supported by appropriate infrastructure, are important elements for containing the spread of COVID-19 in the community.

Construction of the Infection Curve of Local Cases of COVID-19 in Hong Kong using Back-Projection.

This study aimed to estimate the infection curve of local cases of the coronavirus disease (COVID-19) in Hong Kong and identify major events and preventive measures associated with the trajectory of the infection curve in the first two waves. The daily number of onset local cases was used to estimate the daily number of infections based on back-projection. The estimated infection curve was examined to identify the preventive measures or major events associated with its trajectory. Until 30 April 2020, there were 422 confirmed local cases. The infection curve of the local cases in Hong Kong was constructed and used for evaluating the impacts of various policies and events in a narrative manner. Social gatherings and some pre-implementation announcements on inbound traveler policies coincided with peaks on the infection curve.

Using input-output analysis to model the impact of pandemic mitigation and suppression measures on the workforce

The “flatten the curve” graphic has recently become a common tool to visualize the extent to which pandemic suppression and mitigation measures could potentially reduce and delay the number of daily infections due to a pandemic. The COVID-19 pandemic has challenged the capacity of the many healthcare systems and created cascading economic impacts on interdependent sectors of the global society. This paper specifically explores the impact of pandemics on the workforce. The model proposed in this paper comprises of three major steps. First, sources for epidemic curves are identified to generate the attack rate, which is the daily number of infections normalized with respect to the population of the affected region. Second, the model assumes that the general attack rate can be specialized to reflect sector-specific workforce classifications, noting that each economic sector has varying dependence on the workforce. Third, using economic input-output (IO) data from the US Bureau of Economic Analysis, this paper analyzes the performance of several mitigation and suppression measures relative to a baseline pandemic scenario. Results from the IO simulations demonstrate the extent to which mitigation and suppression measures can flatten the curve. This paper concludes with reflections on other consequences of pandemics such as the mental health impacts associated with social isolation and the disproportionate effects on different socioeconomic groups.

Effectiveness of Live Poultry Market Interventions on Human Infection with Avian Influenza A(H7N9) Virus, China.

Various interventions for live poultry markets (LPMs) have emerged to control outbreaks of avian influenza A(H7N9) virus in mainland China since March 2013. We assessed the effectiveness of various LPM interventions in reducing transmission of H7N9 virus across 5 annual waves during 2013–2018, especially in the final wave. With the exception of waves 1 and 4, various LPM interventions reduced daily incidence rates significantly across waves. Four LPM interventions led to a mean reduction of 34%–98% in the daily number of infections in wave 5. Of these, permanent closure provided the most effective reduction in human infection with H7N9 virus, followed by long-period, short-period, and recursive closures in wave 5. The effectiveness of various LPM interventions changed with the type of intervention across epidemics. Permanent LPM closure should be considered to maintain sufficient effectiveness of interventions and prevent the recurrence of H7N9 epidemics.

Asymptotic estimates of SARS-CoV-2 infection counts and their sensitivity to stochastic perturbation.

Despite the importance of having robust estimates of the time-asymptotic total number of infections, early estimates of COVID-19 show enormous fluctuations. Using COVID-19 data from different countries, we show that predictions are extremely sensitive to the reporting protocol and crucially depend on the last available data point before the maximum number of daily infections is reached. We propose a physical explanation for this sensitivity, using a susceptible–exposed–infected–recovered model, where the parameters are stochastically perturbed to simulate the difficulty in detecting patients, different confinement measures taken by different countries, as well as changes in the virus characteristics. Our results suggest that there are physical and statistical reasons to assign low confidence to statistical and dynamical fits, despite their apparently good statistical scores. These considerations are general and can be applied to other epidemics.

Estimating the infection horizon of COVID-19 in eight countries with a data-driven approach.

The COVID-19 pandemic has affected all countries of the world producing a substantial number of fatalities accompanied by a major disruption in their social, financial and educational organization. The strict disciplinary measures implemented by China were very effective and thus were subsequently adopted by most world countries to various degrees. The infection duration and number of infected persons are of critical importance for the battle against the pandemic. We use the quantitative landscape of the disease spreading in China as a benchmark and utilize infection data from eight countries to estimate the complete evolution of the infection in each of these countries. The analysis predicts successfully both the expected number of daily infections per country and, perhaps more importantly, the duration of the epidemic in each country. Our quantitative approach is based on a Gaussian spreading hypothesis that is shown to arise as a result of imposed measures in a simple dynamical infection model. This may have consequences and shed light in the efficiency of policies once the phenomenon is over.

Naive Forecast for COVID-19 in Utah Based on the South Korea and Italy Models-the Fluctuation between Two Extremes.

Differences in jurisdictional public health actions have played a significant role in the relative success of local communities in combating and containing the COVID-19 pandemic. We forecast the possible COVID-19 outbreak in one US state (Utah) by applying empirical data from South Korea and Italy, two countries that implemented disparate public health actions. Forecasts were created by aligning the start of the pandemic in Utah with that in South Korea and Italy, getting a short-run forecast based on actual daily rates of spread, and long-run forecast by employing a log-logistic model with four parameters. Applying the South Korea model, the epidemic peak in Utah is 169 cases/day, with epidemic resolution by the end of May. Applying the Italy model, new cases are forecast to exceed 200/day by mid-April, with the potential for 250 new cases a day at the epidemic peak, with the epidemic continuing through the end of August. We identify a 3-month variation in the likely length of the pandemic, a 1.5-fold difference in the number of daily infections at outbreak peak, and a 3-fold difference in the expected cumulative cases when applying the experience of two developed countries in handling this virus to the Utah context.

Effect of closure of live poultry markets on poultry-to-person transmission of avian influenza A H7N9 virus: an ecological study

Transmission of the novel avian influenza A H7N9 virus seems to be predominantly between poultry and people. In the major Chinese cities of Shanghai, Hangzhou, Huzhou, and Nanjing--where most human cases of infection have occurred--live poultry markets (LPMs) were closed in April, 2013, soon after the initial outbreak, as a precautionary public health measure. Our objective was to quantify the effect of LPM closure in these cities on poultry-to-person transmission of avian influenza A H7N9 virus. We obtained information about every laboratory-confirmed human case of avian influenza A H7N9 virus infection reported in the four cities by June 7, 2013, from a database built by the Chinese Center for Disease Control and Prevention. We used data for age, sex, location, residence type (rural or urban area), and dates of illness onset. We obtained information about LPMs from official sources. We constructed a statistical model to explain the patterns in incidence of cases reported in each city on the basis of the assumption of a constant force of infection before LPM closure, and a different constant force of infection after closure. We fitted the model with Markov chain Monte Carlo methods. 85 human cases of avian influenza A H7N9 virus infection were reported in Shanghai, Hangzhou, Huzhou, and Nanjing by June 7, 2013, of which 60 were included in our main analysis. Closure of LPMs reduced the mean daily number of infections by 99% (95% credibility interval 93-100%) in Shanghai, by 99% (92-100%) in Hangzhou, by 97% (68-100%) in Huzhou, and by 97% (81-100%) in Nanjing. Because LPMs were the predominant source of exposure to avian influenza A H7N9 virus for confirmed cases in these cities, we estimated that the mean incubation period was 3·3 days (1·4-5·7). LPM closures were effective in the control of human risk of avian influenza A H7N9 virus infection in the spring of 2013. In the short term, LPM closure should be rapidly implemented in areas where the virus is identified in live poultry or people. In the long term, evidence-based discussions and deliberations about the role of market rest days and central slaughtering of all live poultry should be renewed. Ministry of Science and Technology, China; Research Fund for the Control of Infectious Disease; Hong Kong University Grants Committee; China-US Collaborative Program on Emerging and Re-emerging Infectious Diseases; Harvard Center for Communicable Disease Dynamics; and the US National Institutes of Health.

Assessment of Intervention Measures for the 2003 SARS Epidemic in Taiwan by Use of a Back-Projection Method

To reconstruct the infection curve for the 2003 severe acute respiratory syndrome (SARS) epidemic in Taiwan and to ascertain the temporal changes in the daily number of infections that occurred during the course of the outbreak. Back-projection method. The peaks of the epidemic correspond well with the occurrence of major infection clusters in the hospitals. The overall downward trend of the infection curve after early May corresponds well to the date (May 10) when changes in the review and classification procedure were implemented by the SARS Prevention and Extrication Committee. The major infection control measures taken by the Taiwanese government over the course of the SARS epidemic, particularly those regarding infection control in hospitals, played a crucial role in containing the outbreak.

Does exercise alter anaerobic threshold in coronary artery disease during beta blockade?

The effect of propranolol on cardiac patients undergoing exercise training is reported to increase exercise tolerance and maximum oxygen uptake (VO2 max) but its effect on anaerobic threshold (AT) is unknown. It was the purpose of this study to determine the role of exercise training with propranolol on AT in patients with coronary artery disease (CAD). Eight men and one woman with significant (CAD) were selected for this study. Each patient completed a maximum treadmill stress test (MTST) following the Bruce protocol on propranolol 40-160 mg/day as a control study. Cardiorespiratory variables were measured at rest and at each stage of the treadmill test. These patients underwent an exercise training programme for 12-16 weeks on the same dose of propranolol. Training sessions were for a minimum of 30-40 minutes, 3 times a week, with training heart rate of 75%-85% of the pretraining peak heart rate. Training heart rate ranged from 98 to 128 beats/min. They were retested with a MTST after the training programme, on the same dose of propranolol. AT was calculated noninvasively by measuring respiratory variables every 30 seconds in relation to work increment. AT was identified by measuring the time course of VE, VCO2, VE/VO2, etc. in relation to incremental work. The mean values of VO2, O2P and % VO2 max at AT before and after training on propanolol were as follows: VO2 = 1.43 L/min +/- .25 and 1.86 L/min +/- .44, O2P = 14.35 +/- 2.40 and 18.73 +/- 4.00 ml/beat, % of VO2 max = 68.20 +/- 6.31 and 73.59 +/- 5.84. The mean changes of VO2 O2P, and % of VO2 max were + 0.43 L/min +/- 0.20 (P < .003), + 4.38 +/- 2.55 (P < .003) and +/- 5.07% +/- 4.84 (P < .001). After exercise training on propanolol, the mean peak exercise tolerance time and absolute VO2 max increased by 2.8 min (from 9.0 to 11.8 min) (P < .001) and 22.7% (P < .007), respectively. We conclude that the increase in anaerobic threshold in patients with coronary artery disease may be due to improvement in VO2 max, increased stroke volume, and peripheral O2 extraction.