scholarly journals China’s effective control and other countries’ uncharted challenge against COVID-19: an epidemiological and modelling study

2020 ◽  
Author(s):  
Lingling Zheng ◽  
Qin Kang ◽  
Weiyao Liao ◽  
Xiujuan Chen ◽  
Shuai Huang ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Reproduction Number ◽  
Case Reports ◽  
Epidemiological Data ◽  
Control Measures ◽  
Time Dependent ◽  
Effective Control ◽  
List Type ◽  
Global Epidemic ◽  
Serial Interval

AbstractBackgroundOn the present trajectory, COVID is inevitably becoming a global epidemic, leading to concerns regarding the pandemic potential in China and other countries.ObjectiveIn this study, we use the time-dependent reproduction number (Rt) to comprise the COVID transmissibility across different countries.MethodsWe used data from Jan 20, 2019, to Feb 29, 2020, on the number of newly confirmed cases, obtained from the reports published by the CDC, to infer the incidence of infectious over time. A two-step procedure was used to estimate the Rt. The first step used data on known index-secondary cases pairs, from publicly available case reports, to estimate the serial interval distribution. The second step estimated the Rt jointly from the incidence data and the information data in the first step. Rt was then used to simulate the epidemics across all major cities in China and typical countries worldwide.ResultsBased on a total of 126 index-secondary cases pairs from 4 international regions, we estimated that the serial interval for SARS-2-CoV was 4.18 (IQR 1.92 – 6.65) days. Domestically, Rt of China, Hubei province, Wuhan had fallen below 1.0 on 9 Feb, 10 Feb and 13 Feb (Rt were 0.99±0.02, 0.99±0.02 and 0.96±0.02), respectively. Internationally, as of 26 Feb, statistically significant periods of COVID spread (Rt >1) were identified for most regions, except for Singapore (Rt was 0.92±0.17).ConclusionsThe epidemic in China has been well controlled, but the worldwide pandemic has not been well controlled. Worldwide preparedness and vulnerability against COVID-19 should be regarded with more care.What is already known on this subject?The basic reproduction number (R0) and the-time-dependent reproduction number (Rt) are two important indicators of infectious disease transmission. In addition, Rt as a derivative of R0 could be used to assess the epidemiological development of the disease and effectiveness of control measures. Most current researches used data from earlier periods in Wuhan and refer to the epidemiological features of SARS, which are possibly biased. Meanwhile, there are fewer studies discussed the Rt of COVID-19. Current clinical and epidemiological data are insufficient to help us understand the full view of the potential transmission of this disease.What this study adds?We use up-to-data observation of the serial interval and cases arising from local transmission to calculate the Rt in different outbreak level area and every province in China as well as five-top sever outbreak countries and other overseas. By comparing the Rt, we discussed the situation of outbreak around the world.

China’s effective control and other countries’ uncharted challenge against COVID-19: an epidemiological and modelling study (Preprint)

2020 ◽  
Author(s):  
Lingling Zheng ◽  
Kang Qin ◽  
Xiujuan Chen ◽  
Shuai Huang ◽  
Dong Liu ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Case Reports ◽  
Effective Control ◽  
Second Step ◽  
Global Epidemic ◽  
Incidence Data ◽  
Step Procedure ◽  
Serial Interval ◽  
More Care ◽  
Interval Distribution

BACKGROUND On the present trajectory, COVID is inevitably becoming a global epidemic, leading to concerns regarding the pandemic potential in China and other countries. OBJECTIVE In this study, we use the time-dependent reproduction number (Rt) to comprise the COVID transmissibility across different countries. METHODS We used data from Jan 20, 2019, to Feb 29, 2020, on the number of newly confirmed cases, obtained from the reports published by the CDC, to infer the incidence of infectious over time. A two-step procedure was used to estimate the Rt. The first step used data on known index-secondary cases pairs, from publicly available case reports, to estimate the serial interval distribution. The second step estimated the Rt jointly from the incidence data and the information data in the first step. Rt was then used to simulate the epidemics across all major cities in China and typical countries worldwide. RESULTS Based on a total of 126 index-secondary cases pairs from 4 international regions, we estimated that the serial interval for SARS-2-CoV was 4.18. Domestically, Rt of China, Hubei province, Wuhan had fallen below 1.0 on 9 Feb, 10 Feb and 13 Feb, respectively. Internationally, as of 26 Feb, statistically significant periods of COVID spread (Rt >1) were identified for most regions, except for Singapore. CONCLUSIONS The epidemic in China has been well controlled, but the worldwide pandemic has not been well controlled. Worldwide preparedness and vulnerability against COVID-19 should be regarded with more care.

scholarly journals China’s effective control and other countries’ uncharted challenge against COVID-19: an epidemiological and modelling study

2020 ◽  
Author(s):  
Lingling Zheng ◽  
Qin Kang ◽  
Xiujuan Chen ◽  
Shuai Huang ◽  
Dong Liu ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Case Reports ◽  
Effective Control ◽  
Second Step ◽  
Incidence Data ◽  
Step Procedure ◽  
Serial Interval ◽  
More Care ◽  
Interval Distribution ◽  
Over Time

Abstract Objective: In this study, we use the time-dependent reproduction number (Rt) to comprise the COVID transmissibility across different countries.Methods: We used data from Jan 20, 2019, to Feb 29, 2020, on the number of newly confirmed cases, obtained from the reports published by the CDC, to infer the incidence of infectious over time. A two-step procedure was used to estimate the Rt. The first step used data on known index-secondary cases pairs, from publicly available case reports, to estimate the serial interval distribution. The second step estimated the Rt jointly from the incidence data and the information data in the first step. Rt was then used to simulate the epidemics across all major cities in China and typical countries worldwide. Results: Based on a total of 126 index-secondary cases pairs from 4 international regions, we estimated that the serial interval for SARS-2-CoV was 4.18 (IQR 1.92 – 6.65) days. Domestically, Rt of China, Hubei province, Wuhan had fallen below 1.0 on 9 Feb, 10 Feb and 13 Feb (Rt were 0.99±0.02, 0.99±0.02 and 0.96±0.02), respectively. Internationally, as of 26 Feb, statistically significant periods of COVID spread (Rt >1) were identified for most regions, except for Singapore (Rt was 0.92±0.17).Conclusions: The epidemic in China has been well controlled, but the worldwide pandemic has not been well controlled. Worldwide preparedness and vulnerability against COVID-19 should be regarded with more care.

scholarly journals Serial interval, basic reproduction number and prediction of COVID-19 epidemic size in Jodhpur, India

2020 ◽  
Author(s):  
Suman Saurabh ◽  
Mahendra Kumar Verma ◽  
Vaishali Gautam ◽  
Akhil Goel ◽  
Manoj Kumar Gupta ◽  
...  
Keyword(s):  
Basic Reproduction Number ◽  
Capacity Planning ◽  
Reproduction Number ◽  
Local Level ◽  
Substantial Reduction ◽  
Control Measures ◽  
Contact Tracing ◽  
Effective Control ◽  
Epidemic Size ◽  
Serial Interval

ABSTRACTBackgroundUnderstanding the epidemiology of COVID-19 is important for design of effective control measures at local level. We aimed to estimate the serial interval and basic reproduction number for Jodhpur, India and to use it for prediction of epidemic size for next one month.MethodsContact tracing of SARS-CoV-2 infected individuals was done to obtain the serial intervals. Aggregate and instantaneous R0 values were derived and epidemic projection was done using R software v4.0.0.ResultsFrom among 79 infector-infectee pairs, the estimated median and 95 percentile values of serial interval were 5.98 days (95% CI 5.39 – 6.65) and 13.17 days (95% CI 11.27 – 15.57), respectively. The overall R0 value in the first 30 days of outbreak was 1.64 (95% CI 1.12 – 2.25) which subsequently decreased to 1.07 (95% CI 1.06 – 1.09). The instantaneous R0 value over 14 days window ranged from a peak of 3.71 (95% CI 1.85 -2.08) to 0.88 (95% CI 0.81 – 0.96) as on 24 June 2020. The projected COVID-19 case-load over next one month was 1881 individuals. Reduction of R0 from 1.17 to 1.085 could result in 23% reduction in projected epidemic size over the next one month.ConclusionAggressive testing, contact-tracing and isolation of infected individuals in Jodhpur district resulted in reduction of R0. Further strengthening of control measures could lead to substantial reduction of COVID-19 epidemic size. A data-driven strategy was found useful in surge capacity planning and guiding the public health strategy at local level.

scholarly journals African Trypanosomiasis Dynamics: Modelling the Effects of Treatment, Education, and Vector Trapping

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yustina A. Liana ◽  
Nyimvua Shaban ◽  
Goodluck Mlay ◽  
Anitha Phibert
Keyword(s):  
Disease Transmission ◽  
Deterministic Model ◽  
Reproduction Number ◽  
Public Health Education ◽  
Tsetse Fly ◽  
Control Measures ◽  
Effective Control ◽  
Tsetse Flies ◽  
Model Parameters ◽  
African Trypanosomiasis

African trypanosomiasis is a vector-borne disease that is mainly transmitted by infected tsetse flies. A deterministic model of tsetse fly vector, human, and cattle hosts is formulated and analyzed to gain insights into the disease dynamics. The roles of public health education, treatment, and tsetse fly traps are studied. The effective reproduction number, a threshold used to determine whether the disease persists or dies out in the population, is determined. The sensitivity analysis of the model parameters is performed to determine their relationship with the effective reproduction number. The results show that the tsetse fly biting rate is the most sensitive parameter to the effective reproduction number. Furthermore, the model’s numerical simulation shows that a combination of all three interventions has the most significant impact on the control of African trypanosomiasis. Thus, we recommend that these control measures be put concurrently in endemic areas for effective control of the disease transmission.

scholarly journals Theoretical investigation of pre-symptomatic SARS-CoV-2 person-to-person transmission in households

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yehuda Arav ◽  
Ziv Klausner ◽  
Eyal Fattal
Keyword(s):  
Scientific Basis ◽  
Control Measures ◽  
Physical Contact ◽  
Effective Control ◽  
Mathematical Framework ◽  
Effective Prevention ◽  
Modes Of Transmission ◽  
Serial Interval ◽  
The Common ◽  
Interval Distribution

AbstractSince its emergence, the phenomenon of SARS-CoV-2 transmission by seemingly healthy individuals has become a major challenge in the effort to achieve control of the pandemic. Identifying the modes of transmission that drive this phenomenon is a perquisite in devising effective control measures, but to date it is still under debate. To address this problem, we have formulated a detailed mathematical model of discrete human actions (such as coughs, sneezes, and touching) and the continuous decay of the virus in the environment. To take into account those discrete and continuous events we have extended the common modelling approach and employed a hybrid stochastic mathematical framework. This allowed us to calculate higher order statistics which are crucial for the reconstruction of the observed distributions. We focused on transmission within a household, the venue with the highest risk of infection and validated the model results against the observed secondary attack rate and the serial interval distribution. Detailed analysis of the model results identified the dominant driver of pre-symptomatic transmission as the contact route via hand-face transfer and showed that wearing masks and avoiding physical contact are an effective prevention strategy. These results provide a sound scientific basis to the present recommendations of the WHO and the CDC.

scholarly journals Chronic Wasting Disease Transmission Risk Assessment for Farmed Cervids in Minnesota and Wisconsin

Viruses ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1586
Author(s):  
James M. Kincheloe ◽  
Dennis N. Makau ◽  
Scott J. Wells ◽  
Amy R. Horn-Delzer
Keyword(s):  
Risk Assessment ◽  
Disease Transmission ◽  
Chronic Wasting Disease ◽  
Control Measures ◽  
Transmission Risk ◽  
Effective Control ◽  
Wasting Disease ◽  
Qualitative Risk Assessment ◽  
Low Uncertainty ◽  
High Uncertainty

CWD (chronic wasting disease) has emerged as one of the most important diseases of cervids and continues to adversely affect farmed and wild cervid populations, despite control and preventive measures. This study aims to use the current scientific understanding of CWD transmission and knowledge of farmed cervid operations to conduct a qualitative risk assessment for CWD transmission to cervid farms and, applying this risk assessment, systematically describe the CWD transmission risks experienced by CWD-positive farmed cervid operations in Minnesota and Wisconsin. A systematic review of literature related to CWD transmission informed our criteria to stratify CWD transmission risks to cervid operations into high-risk low uncertainty, moderate-risk high uncertainty, and negligible-risk low uncertainty categories. Case data from 34 CWD-positive farmed cervid operations in Minnesota and Wisconsin from 2002 to January 2019 were categorized by transmission risks exposure and evaluated for trends. The majority of case farms recorded high transmission risks (56%), which were likely sources of CWD, but many (44%) had only moderate or negligible transmission risks, including most of the herds (62%) detected since 2012. The presence of CWD-positive cervid farms with only moderate or low CWD transmission risks necessitates further investigation of these risks to inform effective control measures.

TRANSMISSION DYNAMICS AND OPTIMAL CONTROL OF AN INFLUENZA MODEL WITH QUARANTINE AND TREATMENT

2012 ◽  
Vol 05 (03) ◽  
pp. 1260011 ◽  
Author(s):  
WEI-WEI SHI ◽  
YUAN-SHUN TAN
Keyword(s):  
Optimal Control ◽  
Disease Transmission ◽  
Reproduction Number ◽  
Influenza Pandemic ◽  
Control Measures ◽  
Globally Asymptotically Stable ◽  
Number Formula ◽  
Parameter Values ◽  
The Impact ◽  
Disease Free

We develop an influenza pandemic model with quarantine and treatment, and analyze the dynamics of the model. Analytical results of the model show that, if basic reproduction number [Formula: see text], the disease-free equilibrium (DFE) is globally asymptotically stable, if [Formula: see text], the disease is uniformly persistent. The model is then extended to assess the impact of three anti-influenza control measures, precaution, quarantine and treatment, by re-formulating the model as an optimal control problem. We focus primarily on controlling disease with a possible minimal the systemic cost. Pontryagin's maximum principle is used to characterize the optimal levels of the three controls. Numerical simulations of the optimality system, using a set of reasonable parameter values, indicate that the precaution measure is more effective in reducing disease transmission than the other two control measures. The precaution measure should be emphasized.

scholarly journals The Effect of Seasonal Weather Variation on the Dynamics of the Plague Disease

2017 ◽  
Vol 2017 ◽  
pp. 1-25 ◽  
Author(s):  
Rigobert C. Ngeleja ◽  
Livingstone S. Luboobi ◽  
Yaw Nkansah-Gyekye
Keyword(s):  
Basic Reproduction Number ◽  
Disease Transmission ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Weather Conditions ◽  
Effective Control ◽  
Human Beings ◽  
Weather Variation ◽  
The Basic Reproduction Number ◽  
Seasonal Weather

Plague is a historic disease which is also known to be the most devastating disease that ever occurred in human history, caused by gram-negative bacteria known as Yersinia pestis. The disease is mostly affected by variations of weather conditions as it disturbs the normal behavior of main plague disease transmission agents, namely, human beings, rodents, fleas, and pathogens, in the environment. This in turn changes the way they interact with each other and ultimately leads to a periodic transmission of plague disease. In this paper, we formulate a periodic epidemic model system by incorporating seasonal transmission rate in order to study the effect of seasonal weather variation on the dynamics of plague disease. We compute the basic reproduction number of a proposed model. We then use numerical simulation to illustrate the effect of different weather dependent parameters on the basic reproduction number. We are able to deduce that infection rate, progression rates from primary forms of plague disease to more severe forms of plague disease, and the infectious flea abundance affect, to a large extent, the number of bubonic, septicemic, and pneumonic plague infective agents. We recommend that it is more reasonable to consider these factors that have been shown to have a significant effect on RT for effective control strategies.

scholarly journals Frequency and distribution of neglected tropical diseases in Mozambique: a systematic review

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Berta Grau-Pujol ◽  
Marilia Massangaie ◽  
Jorge Cano ◽  
Carmen Maroto ◽  
Alcino Ndeve ◽  
...  
Keyword(s):  
Systematic Review ◽  
Neglected Tropical Diseases ◽  
Case Reports ◽  
Grey Literature ◽  
Case Series ◽  
Epidemiological Data ◽  
Effective Control ◽  
Tropical Diseases ◽  
Case Control Studies ◽  
Cross Sectional

Abstract Background Neglected tropical diseases (NTDs) affect more than one billion people living in vulnerable conditions. In spite of initiatives recently contributing to fill NTDs gaps on national and local prevalence and distribution, more epidemiological data are still needed for effective control and elimination interventions. Main text Mozambique is considered one of the countries with highest NTDs burden although available data is scarce. This study aims to conduct a systematic review on published available data about the burden and distribution of the different NTDs across Mozambique since January 1950 until December 2018. We identified manuscripts from electronic databases (Pubmed, EmBase and Global Health) and paper publications and grey literature from Mozambique Ministry of Health. Manuscripts fulfilling inclusion criteria were: cross-sectional studies, ecological studies, cohorts, reports, systematic reviews, and narrative reviews capturing epidemiological information of endemic NTDs in Mozambique. Case-control studies, letters to editor, case reports and case series of imported cases were excluded. A total of 466 manuscripts were initially identified and 98 were finally included after the revision following PRISMA guidelines. Eleven NTDs were reported in Mozambique during the study span. Northern provinces (Nampula, Cabo Delgado, Niassa, Tete and Zambezia) and Maputo province had the higher number of NTDs detected. Every disease had their own report profile: while schistosomiasis have been continuously reported since 1952 until nowadays, onchocerciasis and cysticercosis last available data is from 2007 and Echinococcosis have never been evaluated in the country. Thus, both space and time gaps on NTDs epidemiology have been identified. Conclusions This review assembles NTDs burden and distribution in Mozambique. Thus, contributes to the understanding of NTDs epidemiology in Mozambique and highlights knowledge gaps. Hence, the study provides key elements to progress towards the control and interruption of transmission of these diseases in the country.

scholarly journals On realized serial and generation intervals given control measures: The COVID-19 pandemic case

2021 ◽  
Vol 17 (3) ◽  
pp. e1008892
Author(s):  
Andrea Torneri ◽  
Pieter Libin ◽  
Gianpaolo Scalia Tomba ◽  
Christel Faes ◽  
James G. Wood ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Transmission Probability ◽  
Theoretical Explanation ◽  
Control Measures ◽  
Strong Impact ◽  
Generation Interval ◽  
Incidence Data ◽  
Intervention Measures ◽  
Serial Interval ◽  
The Mean

The SARS-CoV-2 pathogen is currently spreading worldwide and its propensity for presymptomatic and asymptomatic transmission makes it difficult to control. The control measures adopted in several countries aim at isolating individuals once diagnosed, limiting their social interactions and consequently their transmission probability. These interventions, which have a strong impact on the disease dynamics, can affect the inference of the epidemiological quantities. We first present a theoretical explanation of the effect caused by non-pharmaceutical intervention measures on the mean serial and generation intervals. Then, in a simulation study, we vary the assumed efficacy of control measures and quantify the effect on the mean and variance of realized generation and serial intervals. The simulation results show that the realized serial and generation intervals both depend on control measures and their values contract according to the efficacy of the intervention strategies. Interestingly, the mean serial interval differs from the mean generation interval. The deviation between these two values depends on two factors. First, the number of undiagnosed infectious individuals. Second, the relationship between infectiousness, symptom onset and timing of isolation. Similarly, the standard deviations of realized serial and generation intervals do not coincide, with the former shorter than the latter on average. The findings of this study are directly relevant to estimates performed for the current COVID-19 pandemic. In particular, the effective reproduction number is often inferred using both daily incidence data and the generation interval. Failing to account for either contraction or mis-specification by using the serial interval could lead to biased estimates of the effective reproduction number. Consequently, this might affect the choices made by decision makers when deciding which control measures to apply based on the value of the quantity thereof.

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