scholarly journals Effects of control measures and their importance on COVID-19 transmission dynamics

2021 ◽  
Author(s):  
Chonawee Supatgiat
Keyword(s):  
Early Stage ◽  
Markov Chain Model ◽  
Face Mask ◽  
School Closure ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Effective Control ◽  
Chain Model ◽  
Testing Protocols

Abstract For more than a year, governments around the world have attempted to control the COVID-19 pandemic. Control measures such as social distancing, face mask wearing, business/school closure, city or transportation lockdown, ban of mass gathering, population education and engagement, contact tracing, and improved mass testing protocols are being used to contain the pandemic. Currently, there are no studies to date that rank the importance of these measures so that the governments may allocate and target their resources towards the most effective control measures. In this paper, we propose a Discrete Time Markov Chain model that captures the above control measures and ranks them. We also show that the importance of the measures change overtime and depends on the stage of the transmission dynamics, as well as the environment. For example, contract tracing is known to be a powerful measure to effectively control the pandemic, however its influence is dynamic in nature. Our results show that contact tracing is indeed helpful during the early stage of the pandemic, but becomes less important after a vaccination program takes effect. If implemented, our novel and unique model may assist many countries in their crucial pandemic control decisions.

scholarly journals Effects of control measures and their impacts on COVID-19 transmission dynamics

2021 ◽  
Author(s):  
Chonawee Supatgiat
Keyword(s):  
Markov Chain Model ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Chain Model ◽  
School Closures ◽  
Public Places ◽  
Discrete Time Markov Chain ◽  
Changes Over Time ◽  
Testing Protocols

Abstract Governments around the world have grappled with the COVID-19 pandemic for more than a year. Control measures such as social distancing, use of face masks in public places, business and school closures, city or transportation lockdowns, mass gathering bans, population education and engagement, contact tracing, and improved mass testing protocols are being used to contain the pandemic. Currently, there are no studies to date that rank the effectiveness of these measures, resulting in government responses that may be uncoordinated and inefficient. In this study, we developed a Discrete Time Markov Chain model that captures the above control measures and ranks them. We found that the importance of the measures changes over time and depends on the stage of transmission dynamics, as well as the ecological environment. For example, contact tracing is a powerful measure to effectively control the pandemic, however, our results show that while it is indeed helpful during the early stages of the pandemic, it is much less important after a vaccination program takes effect. Besides, our model improved the standard SEIR compartmental model by taking into account the dynamic temporal transmission and recovery probabilities along with considering a portion of the population that will not comply with government-mandated control measures. If implemented, our novel and unique model may assist many countries in pandemic control decisions.

scholarly journals Effects of case- and population-based COVID-19 interventions in Taiwan

2020 ◽  
Author(s):  
Ta-Chou V Ng ◽  
Hao-Yuan Cheng ◽  
Hsiao-Han Chang ◽  
Cheng-Chieh Liu ◽  
Chih-Chi Yang ◽  
...  
Keyword(s):  
Early Stage ◽  
Critical Role ◽  
Face Mask ◽  
Population Based ◽  
School Closure ◽  
Contact Tracing ◽  
Travel Restrictions ◽  
The Government ◽  
Border Controls ◽  
Case Based

In the first wave of the COVID-19 pandemic, broad usage of non-pharmaceutical interventions played a crucial role in controlling epidemics. However, the substantial economic and societal costs of continuous use of border controls, travel restrictions, and physical distancing measures suggest that these measures may not be sustainable and that policymakers have to seek strategies to lift the restrictions. Taiwan was one of the few countries that demonstrated initial success in eliminating the COVID-19 outbreak without strict lockdown or school closure. To understand the key contributors to the successful control, we applied a stochastic branching model to empirical case data to evaluate and compare the effectiveness of more targeted case-based (including contact tracing and quarantine) and less targeted population-based interventions (including social distancing and face mask use) in Taiwan. We found that case-based interventions alone would not be sufficient to contain the epidemic, even in a setting where a highly efficient contact tracing program was in place. The voluntary population-based interventions have reduced the reproduction numbers by more than 60% and have likely played a critical role at the early stage of the outbreak. Our analysis of Taiwan's success highlights that coordinated efforts from both the government and the citizens are indispensable in the fight against COVID-19 pandemic.

scholarly journals Effectiveness of Epidemic Preventive Policies and Hospital Strategies in Combating COVID-19 Outbreak in Taiwan

2021 ◽  
Vol 18 (7) ◽  
pp. 3456
Author(s):  
Ting Wan Tan ◽  
Han Ling Tan ◽  
Man Na Chang ◽  
Wen Shu Lin ◽  
Chih Ming Chang
Keyword(s):  
Mortality Rate ◽  
Incidence Rate ◽  
Risk Ratio ◽  
Early Stage ◽  
Control Measures ◽  
Polymerase Chain Reaction Test ◽  
Effective Control ◽  
Nasopharyngeal Swab ◽  
Preventive Strategies ◽  
Epidemic Control

(1) Background: The implementation of effective control measures in a timely fashion is crucial to control the epidemic outbreak of COVID-19. In this study, we aimed to analyze the control measures implemented during the COVID-19 outbreak, as well as evaluating the responses and outcomes at different phases for epidemic control in Taiwan. (2) Methods: This case study reviewed responses to COVID-19 and the effectiveness of a range of control measures implemented for epidemic control in Taiwan and assessed all laboratory-confirmed cases between 11 January until 20 December 2020, inclusive of these dates. The confirmation of COVID-19 infection was defined as the positive result of a reverse-transcriptase–polymerase-chain-reaction test taken from a nasopharyngeal swab. Test results were reported by the Taiwan Centers for Disease Control. The incidence rate, mortality rate, and testing rate were compiled, and the risk ratio was provided to gain insights into the effectiveness of prevention measures. (3) Results and Discussion: This study presents retrospective data on the COVID-19 incidence rate in Taiwan, combined with the vital preventive control measures, in a timeline of the early stage of the epidemic that occurred in Taiwan. The implementation of multiple strategy control measures and the assistance of technologies to control the COVID-19 epidemic in Taiwan led to a relatively slower trend in the outbreak compared to the neighboring countries. In Taiwan, 766 confirmed patients were included, comprised of 88.1% imported cases and 7.2% local transmission cases, within the studied period. The incidence rate of COVID-19 in Taiwan during the studied period was 32 per million people, with a mortality rate of 0.3 per million people. Our analysis showed a significantly raised incidence risk ratio in the countries of interest in comparison to Taiwan during the study period; in the range of 1.9 to 947.5. The outbreak was brought under control through epidemic policies and hospital strategies implemented by the Taiwan Government. (4) Conclusion: Taiwan’s preventive strategies resulted in a drastically lower risk for Taiwan nationals of contracting COVID-19 when new pharmaceutical drug or vaccines were not yet available. The preventive strategies employed by Taiwan could serve as a guide and reference for future epidemic control strategies.

scholarly journals COVID-19 Pandemic Response Simulation in a Large City: Impact of Nonpharmaceutical Interventions on Reopening Society

2021 ◽  
pp. 0272989X2110030
Author(s):  
Serin Lee ◽  
Zelda B. Zabinsky ◽  
Judith N. Wasserheit ◽  
Stephen M. Kofsky ◽  
Shan Liu
Keyword(s):  
Large City ◽  
Face Mask ◽  
School Closure ◽  
Contact Tracing ◽  
The Novel ◽  
Agent Based ◽  
Social Distancing ◽  
Variable Compliance ◽  
Novel Coronavirus ◽  
Nonpharmaceutical Interventions

As the novel coronavirus (COVID-19) pandemic continues to expand, policymakers are striving to balance the combinations of nonpharmaceutical interventions (NPIs) to keep people safe and minimize social disruptions. We developed and calibrated an agent-based simulation to model COVID-19 outbreaks in the greater Seattle area. The model simulated NPIs, including social distancing, face mask use, school closure, testing, and contact tracing with variable compliance and effectiveness to identify optimal NPI combinations that can control the spread of the virus in a large urban area. Results highlight the importance of at least 75% face mask use to relax social distancing and school closure measures while keeping infections low. It is important to relax NPIs cautiously during vaccine rollout in 2021.

scholarly journals Experiential learnings from the Nipah virus outbreaks in Kerala towards containment of infectious public health emergencies in India

2020 ◽  
Vol 148 ◽  
Author(s):  
Rima R. Sahay ◽  
Pragya D. Yadav ◽  
Nivedita Gupta ◽  
Anita M. Shete ◽  
Chandni Radhakrishnan ◽  
...  
Keyword(s):  
State Government ◽  
Single Case ◽  
Point Of Care ◽  
Nipah Virus ◽  
Case Fatality ◽  
Control Measures ◽  
Contact Tracing ◽  
Effective Control ◽  
Hospital Infection Control ◽  
Kerala State

Abstract Nipah virus (NiV) outbreak occurred in Kozhikode district, Kerala, India in 2018 with a case fatality rate of 91% (21/23). In 2019, a single case with full recovery occurred in Ernakulam district. We described the response and control measures by the Indian Council of Medical Research and Kerala State Government for the 2019 NiV outbreak. The establishment of Point of Care assays and monoclonal antibodies administration facility for early diagnosis, response and treatment, intensified contact tracing activities, bio-risk management and hospital infection control training of healthcare workers contributed to effective control and containment of NiV outbreak in Ernakulam.

scholarly journals Using a stochastic continuous-time Markov chain model to examine alternative timing and duration of the COVID-19 lockdown in Kuwait: what can be done now?

2022 ◽  
Vol 80 (1) ◽  
Author(s):  
Mustafa Al-Zoughool ◽  
Tamer Oraby ◽  
Harri Vainio ◽  
Janvier Gasana ◽  
Joseph Longenecker ◽  
...  
Keyword(s):  
Markov Chain ◽  
Continuous Time ◽  
Disease Transmission ◽  
Markov Chain Model ◽  
Substantial Reduction ◽  
Control Measures ◽  
Optimal Timing ◽  
Chain Model ◽  
Continuous Time Markov Chain ◽  
Epidemic Curve

Abstract Background Kuwait had its first COVID-19 in late February, and until October 6, 2020 it recorded 108,268 cases and 632 deaths. Despite implementing one of the strictest control measures-including a three-week complete lockdown, there was no sign of a declining epidemic curve. The objective of the current analyses is to determine, hypothetically, the optimal timing and duration of a full lockdown in Kuwait that would result in controlling new infections and lead to a substantial reduction in case hospitalizations. Methods The analysis was conducted using a stochastic Continuous-Time Markov Chain (CTMC), eight state model that depicts the disease transmission and spread of SARS-CoV 2. Transmission of infection occurs between individuals through social contacts at home, in schools, at work, and during other communal activities. Results The model shows that a lockdown 10 days before the epidemic peak for 90 days is optimal but a more realistic duration of 45 days can achieve about a 45% reduction in both new infections and case hospitalizations. Conclusions In the view of the forthcoming waves of the COVID19 pandemic anticipated in Kuwait using a correctly-timed and sufficiently long lockdown represents a workable management strategy that encompasses the most stringent form of social distancing with the ability to significantly reduce transmissions and hospitalizations.

scholarly journals Estimating transmission dynamics and serial interval of the first wave of COVID-19 infections under different control measures: A statistical analysis in Tunisia from February 29 to May 5, 2020

2020 ◽  
Author(s):  
Khouloud Talmoudi ◽  
Mouna Safer ◽  
Hejer Letaief ◽  
Aicha Hchaichi ◽  
Chahida Harizi ◽  
...  
Keyword(s):  
Emerging Diseases ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Epidemic Threshold ◽  
Illness Onset ◽  
Intervention Measures ◽  
Temporal Reproduction ◽  
Prevention Measure ◽  
Serial Interval

Abstract Background Describing transmission dynamics of the outbreak and impact of intervention measures are critical to planning responses to future outbreaks and providing timely information to guide policy makers decision. We estimate serial interval (SI) and temporal reproduction number (Rt) of SARS-CoV-2 in Tunisia. Methods We collected data of investigations and contact tracing between March 1, 2020 and May 5, 2020 as well as illness onset data during the period February 29-May 5, 2020 from National Observatory of New and Emerging Diseases of Tunisia. Maximum likelihood (ML) approach is used to estimate dynamics of Rt. Results 491 of infector-infectee pairs were involved, with 14.46% reported pre-symptomatic transmission. SI follows Gamma distribution with mean 5.30 days [95% CI 4.66–5.95] and standard deviation 0.26 [95% CI 0.23–0.30]. Also, we estimated large changes in Rt in response to the combined lockdown interventions. The Rt moves from 3.18 [95% CI 2.73–3.69] to 1.77 [95% CI 1.49–2.08] with curfew prevention measure, and under the epidemic threshold (0.89 [95% CI 0.84–0.94]) by national lockdown measure. Conclusions Overall, our findings highlight contribution of interventions to interrupt transmission of SARS-CoV-2 in Tunisia.

scholarly journals Estimating transmission dynamics and serial interval of the first wave of COVID-19 infections under different control measures: a statistical analysis in Tunisia from February 29 to May 5, 2020

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Khouloud Talmoudi ◽  
Mouna Safer ◽  
Hejer Letaief ◽  
Aicha Hchaichi ◽  
Chahida Harizi ◽  
...  
Keyword(s):  
Credible Interval ◽  
Emerging Diseases ◽  
Control Measures ◽  
Transmission Dynamics ◽  
Contact Tracing ◽  
Epidemic Threshold ◽  
Illness Onset ◽  
Intervention Measures ◽  
Temporal Reproduction ◽  
Serial Interval

Abstract Background Describing transmission dynamics of the outbreak and impact of intervention measures are critical to planning responses to future outbreaks and providing timely information to guide policy makers decision. We estimate serial interval (SI) and temporal reproduction number (Rt) of SARS-CoV-2 in Tunisia. Methods We collected data of investigations and contact tracing between March 1, 2020 and May 5, 2020 as well as illness onset data during the period February 29–May 5, 2020 from National Observatory of New and Emerging Diseases of Tunisia. Maximum likelihood (ML) approach is used to estimate dynamics of Rt. Results Four hundred ninety-one of infector-infectee pairs were involved, with 14.46% reported pre-symptomatic transmission. SI follows Gamma distribution with mean 5.30 days [95% Confidence Interval (CI) 4.66–5.95] and standard deviation 0.26 [95% CI 0.23–0.30]. Also, we estimated large changes in Rt in response to the combined lockdown interventions. The Rt moves from 3.18 [95% Credible Interval (CrI) 2.73–3.69] to 1.77 [95% CrI 1.49–2.08] with curfew prevention measure, and under the epidemic threshold (0.89 [95% CrI 0.84–0.94]) by national lockdown measure. Conclusions Overall, our findings highlight contribution of interventions to interrupt transmission of SARS-CoV-2 in Tunisia.

scholarly journals Serum metabolomics in chickens infected with Cryptosporidium baileyi

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Xue-Mei Wu ◽  
Xin Yang ◽  
Xian-Cheng Fan ◽  
Xi Chen ◽  
Yu-Xin Wang ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Early Stage ◽  
Control Measures ◽  
Sphingolipid Metabolism ◽  
Effective Control ◽  
Serum Samples ◽  
Multivariate Statistical ◽  
The Impact ◽  
Cryptosporidium Baileyi

Abstract Background Cryptosporidium baileyi is an economically important zoonotic pathogen that causes serious respiratory symptoms in chickens for which no effective control measures are currently available. An accumulating body of evidence indicates the potential and usefulness of metabolomics to further our understanding of the interaction between pathogens and hosts, and to search for new diagnostic or pharmacological biomarkers of complex microorganisms. The aim of this study was to identify the impact of C. baileyi infection on the serum metabolism of chickens and to assess several metabolites as potential diagnostic biomarkers for C. baileyi infection. Methods Ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) and subsequent multivariate statistical analysis were applied to investigate metabolomics profiles in the serum samples of chickens infected with C. baileyi, and to identify potential metabolites that can be used to distinguish chickens infected with C. baileyi from non-infected birds. Results Multivariate statistical analysis identified 138 differential serum metabolites between mock- and C. baileyi-infected chickens at 5 days post-infection (dpi), including 115 upregulated and 23 downregulated compounds. These metabolites were significantly enriched into six pathways, of which two pathways associated with energy and lipid metabolism, namely glycerophospholipid metabolism and sphingolipid metabolism, respectively, were the most enriched. Interestingly, some important immune-related pathways were also significantly enriched, including the intestinal immune network for IgA production, autophagy and cellular senescence. Nine potential C. baileyi-responsive metabolites were identified, including choline, sirolimus, all-trans retinoic acid, PC(14:0/22:1(13Z)), PC(15:0/22:6(4Z,7Z,10Z,13Z,16Z,19Z)), PE(16:1(9Z)/24:1(15Z)), phosphocholine, SM(d18:0/16:1(9Z)(OH)) and sphinganine. Conclusions This is the first report on serum metabolic profiling of chickens with early-stage C. baileyi infection. The results provide novel insights into the pathophysiological mechanisms of C. baileyi in chickens. Graphic abstract

scholarly journals Using a Stochastic Continuous-Time Markov Chain Model to Examine Alternative Timing and Duration of the COVID-19 Lockdown in Kuwait: What Can be Done Now?

2021 ◽  
Author(s):  
Mustafa Al-Zoughool ◽  
Tamer Oraby ◽  
Harri Vainio ◽  
Janvier Gasana ◽  
Joseph Longnecker ◽  
...  
Keyword(s):  
Markov Chain ◽  
Continuous Time ◽  
Disease Transmission ◽  
Markov Chain Model ◽  
Substantial Reduction ◽  
Control Measures ◽  
Optimal Timing ◽  
Chain Model ◽  
Continuous Time Markov Chain ◽  
Epidemic Curve

Abstract Background: Kuwait had its first COVID-19 in late February, and until October 6, 2020 it recorded 108,268 cases and 632 deaths. Despite implementing one of the strictest control measures-including a three-week complete lockdown, there was no sign of a declining epidemic curve. The objective of the current analyses is to determine, hypothetically, the optimal timing and duration of a full lockdown in Kuwait that would result in controlling new infections and lead to a substantial reduction in case hospitalizations. Methods: The analysis was conducted using a stochastic Continuous-Time Markov Chain (CTMC), eight state model that depicts the disease transmission and spread of SARS-CoV 2. Transmission of infection occurs between individuals through social contacts at home, in schools, at work, and during other communal activities. Results: The model shows that a lockdown 10 days before the epidemic peak for 90 days is optimal but a more realistic duration of 45 days can achieve about a 45% reduction in both new infections and case hospitalizations.Conclusions: In the view of the forthcoming waves of the COVID19 pandemic anticipated in Kuwait using a correctly-timed and sufficiently long lockdown represents a workable management strategy that encompasses the most stringent form of social distancing with the ability to significantly reduce transmissions and hospitalizations.

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