Role of the Health Department in Tuberculosis Prevention and Control—Legal and Public Health Considerations

Jeffries, Carla; Lobue, Phil; Chorba, Terence; Metchock, Beverly; Kashef, Ijaz

doi:10.1128/microbiolspec.tnmi7-0034-2016

Cited by 8 publications

(9 citation statements)

References 22 publications

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“…The government should take responsibility for general infection control, including information collection, distribution of resources, training, education, and decision-making with regard to the infection control policy at national level [6]. Effective prevention and control of infection requires data sharing via a suitable platform [7].…”

Section: What Did We Learn From This New Model?mentioning

confidence: 99%

A new model for COVID-19 control and its implementation in the city of Honghu, China: a case report

Wang

Gong

Sun

et al. 2021

Antimicrob Resist Infect Control

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Background Novel coronavirus pneumonia has been the most serious worldwide public health emergency since being identified in December 2019. The rapid spread of the pandemic and the strong human to human infection rate of COVID-19 poses a great prevention challenge. There has been an explosion in the number of confirmed cases in several cities near Wuhan, including the highest in Honghu, Jinzhou. Owing to the limited admission capacity and medical resources, increasing numbers of suspected cases of COVID-19 infection were difficult to confirm or treat. Case presentation Following the arrival of the Guangdong medical aid team on 11 February, 2020, COVID-19 care in Honghu saw changes after a series of solutions were implemented based on the ‘Four-Early’ and ‘Four-centralization’ management measures. The ‘Four-Early’ measures are: early detection, early reporting, early quarantine, and early treatment for meeting an urgent need like the COVID-19 pandemic. ‘Four-centralization’ refers to the way in which recruited medical teams can make full use of medical resources to give patients the best treatment. These solutions successfully increased the recovery rate and reduced mortality among patients with COVID-19 in Honghu. Conclusions This management strategy is called the ‘Honghu Model’ which can be generalized to enable the prevention and management of COVID-19 worldwide.

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Section: What Did We Learn From This New Model?mentioning

confidence: 99%

A new model for COVID-19 control and its implementation in the city of Honghu, China: a case report

Wang

Gong

Sun

et al. 2021

Antimicrob Resist Infect Control

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show abstract

“…2 Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, 130012, Changchun, China. 3 College of Software, Jilin University, 130012, Changchun, China. 4 Graduate School of Engineering, Nagasaki Institute of Applied Science, 536 Aba-machi, 851-0193, Nagasaki, Japan.…”

Section: Availability Of Data and Materialsmentioning

confidence: 99%

“…Therefore, it is necessary to predict the incidence of TB accurately. The provincial epidemic prevention and control center can evaluate the scale of the epidemic according to the forecast results of incidence rate, and adopt corresponding measures for different areas [3,4].…”

Section: Introductionmentioning

confidence: 99%

A Multivariate Multi-Step LSTM Forecasting Model for Tuberculosis Incidence With Model Explanation in Liaoning Province, China

Yang¹

2021

Preprint

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Purpose: In addition to COVID-19, tuberculosis (TB) is the respiratory infectious disease with the highest incidence in China. We aim to design a series of forecasting models and find the factors that affect the incidence of TB, thereby improving the accuracy of the incidence prediction. Results: In this paper, we developed a new interpretable prediction system based on the multivariate multi-step Long Short-Term Memory (LSTM) model and SHapley Additive exPlanation (SHAP) method. Moreover, four accuracy measures are introduced into the system: Root Mean Square Error, Mean Absolute Error, Mean Absolute Percentage Error, and symmetric Mean Absolute Percentage Error. Meanwhile, the Autoregressive Integrated Moving Average (ARIMA) model and seasonal ARIMA model are established. The multi-step ARIMA-LSTM model is proposed for the first time to examine the performance of each model in the short, medium, and long term, respectively. Compared with the ARIMA model, each error of the multivariate 2-step LSTM model is reduced by 12.92%, 15.94%, 15.97%, and 14.81% in the short term. The 3-step ARIMA-LSTM model achieved excellent performance, with each error decreased to 15.19%, 33.14%, 36.79%, and 29.76% in the medium and long term. We provide the local and global explanation of the multivariate single-step LSTM model in the field of incidence prediction, pioneering. Conclusion: The multivariate 2-step LSTM model is suitable for short-term forecasts, and the 3-step ARIMA-LSTM model is appropriate for medium- and long-term forecasts. In addition, the prediction effect was better than similar TB incidence forecasting models. The SHAP results indicate that the five most crucial features are maximum temperature, average relative humidity, local financial budget, monthly sunshine percentage, and sunshine hours.

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“…In the United States, the control of TB infections is a multifaceted process involving employees in the private health care sector; federal agencies, such as the Centers for Disease Control and Prevention's (CDC) and well as state and local health departments [64,65]. It is very important to involve local health departments as 77% of US-diagnosed TB patients receive most or all of their clinical care through these facilities [66].…”

Section: Important Factors In M Tuberculosis Infections and Limitatimentioning

confidence: 99%

The War against Tuberculosis: A Review of Natural Compounds and Their Derivatives

et al. 2020

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Tuberculosis (TB), caused by the bacterial organism Mycobacterium tuberculosis, pose a major threat to public health, especially in middle and low-income countries. Worldwide in 2018, approximately 10 million new cases of TB were reported to the World Health Organization (WHO). There are a limited number of medications available to treat TB; additionally, multi-drug resistant TB and extensively-drug resistant TB strains are becoming more prevalent. As a result of various factors, such as increased costs of developing new medications and adverse side effects from current medications, researchers continue to evaluate natural compounds for additional treatment options. These substances have the potential to target bacterial cell structures and may contribute to successful treatment. For example, a study reported that green and black tea, which contains epigallocatechin gallate (a phenolic antioxidant), may decrease the risk of contracting TB in experimental subjects; cumin (a seed from the parsley plant) has been demonstrated to improve the bioavailability of rifampicin, an important anti-TB medication, and propolis (a natural substance produced by honeybees) has been shown to improve the binding affinity of anti-TB medications to bacterial cell structures. In this article, we review the opportunistic pathogen M. tuberculosis, various potential therapeutic targets, available therapies, and natural compounds that may have anti-TB properties. In conclusion, different natural compounds alone as well as in combination with already approved medication regimens should continue to be investigated as treatment options for TB.

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Role of the Health Department in Tuberculosis Prevention and Control—Legal and Public Health Considerations

Cited by 8 publications

References 22 publications

A new model for COVID-19 control and its implementation in the city of Honghu, China: a case report

A new model for COVID-19 control and its implementation in the city of Honghu, China: a case report

A Multivariate Multi-Step LSTM Forecasting Model for Tuberculosis Incidence With Model Explanation in Liaoning Province, China

The War against Tuberculosis: A Review of Natural Compounds and Their Derivatives

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