Modelling bluetongue risk in Kazakhstan

Abstract Background Bluetongue is a serious disease of ruminants caused by the bluetongue virus (BTV). BTV is transmitted by biting midges (Culicoides spp.). Serological evidence from livestock and the presence of at least one competent vector species of Culicoides suggests that transmission of BTV is possible and may have occurred in Kazakhstan. Methods We estimated the risk of transmission using a mathematical model of the reproduction number R0 for bluetongue. This model depends on livestock density and climatic factors which affect vector density. Data on climate and livestock numbers from the 2466 local communities were used. This, together with previously published model parameters, was used to estimate R0 for each month of the year. We plotted the results on isopleth maps of Kazakhstan using interpolation to smooth the irregular data. We also mapped the estimated proportion of the population requiring vaccination to prevent outbreaks of bluetongue. Results The results suggest that transmission of bluetongue in Kazakhstan is not possible in the winter from October to March. Assuming there are vector-competent species of Culicoides endemic in Kazakhstan, then low levels of risk first appear in the south of Kazakhstan in April before spreading north and intensifying, reaching maximum levels in northern Kazakhstan in July. The risk declined in September and had disappeared by October. Conclusion These results should aid in surveillance efforts for the detection and control of bluetongue in Kazakhstan by indicating where and when outbreaks of bluetongue are most likely to occur. The results also indicate where vaccination efforts should be focussed to prevent outbreaks of disease. Graphical abstract

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Modelling Bluetongue Risk in Kazakhstan

10.21203/rs.3.rs-76231/v1 ◽

2020 ◽

Author(s):

Sarsenbay Abdrakmanov ◽

Beisembayev Kanatzhan ◽

Akmetzhan Sultanov ◽

Yersyn Mukhanbetkaliyev ◽

Ablaikhan Kadyrov ◽

...

Keyword(s):

Relative Risk ◽

Climatic Factors ◽

Model Parameters ◽

Biting Midges ◽

Density Estimates ◽

Relative Risks ◽

Livestock Density ◽

Low Levels ◽

Serious Disease ◽

And Control

Abstract Background: Bluetongue is a serious disease of ruminants transmitted by biting midges (Culicoides spp). Serological evidence from livestock and the presence of at least one vector competent spp of Culicoides suggests that transmission of bluetongue is possible and may have occurred in Kazakhstan. Methods: We estimated the relative risk of transmission using a mathematical model of the reproduction number R0 for bluetongue. This model depends on livestock density and climatic factors which affect vector density. Data on climate and livestock numbers from the 2778 local communities were used. This together with previously published model parameters was used to estimate R0 for each month of the year, which was rescaled to give a relative risk of transmission. These relative risks were mapped using kernal density estimates using R statistical software and mapping tools.Results: The results suggest that transmission of bluetongue in Kazakhstan is not possible in the winter from November to March. Assuming there are vector competent species of Culicoides endemic in Kazakhstan, then low levels of risk first appear in the south of Kazakhstan in April before spreading north and intensifying reaching maximum levels in northern Kazakhstan in August. The risk decline in September with only a low risk of transmission in October.Conclusion: These results should aid in surveillance efforts for the detection and control of bluetongue in Kazakhstan by indicating where and when outbreaks of bluetongue are most likely to occur.

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Modelling Bluetongue Risk in Kazakhstan

10.21203/rs.3.rs-97709/v1 ◽

2020 ◽

Author(s):

Sarsenbay Abdrakhmanov ◽

Beisembayev Kanatzhan ◽

Akmetzhan Sultanov ◽

Yersyn Mukhanbetkaliyev ◽

Ablaikhan Kadyrov ◽

...

Keyword(s):

Relative Risk ◽

Climatic Factors ◽

Model Parameters ◽

Biting Midges ◽

Density Estimates ◽

Relative Risks ◽

Livestock Density ◽

Low Levels ◽

Serious Disease ◽

And Control

Abstract Background: Bluetongue is a serious disease of ruminants transmitted by biting midges (Culicoides spp). Serological evidence from livestock and the presence of at least one vector competent spp of Culicoides suggests that transmission of bluetongue is possible and may have occurred in Kazakhstan. Methods: We estimated the relative risk of transmission using a mathematical model of the reproduction number R0 for bluetongue. This model depends on livestock density and climatic factors which affect vector density. Data on climate and livestock numbers from the 2466 local communities were used. This together with previously published model parameters was used to estimate R0 for each month of the year, which was rescaled to give a relative risk of transmission. These relative risks were mapped using kernal density estimates using R statistical software and mapping tools.Results: The results suggest that transmission of bluetongue in Kazakhstan is not possible in the winter from November to March. Assuming there are vector competent species of Culicoides endemic in Kazakhstan, then low levels of risk first appear in the south of Kazakhstan in April before spreading north and intensifying reaching maximum levels in northern Kazakhstan in August. The risk decline in September with only a low risk of transmission in October.Conclusion: These results should aid in surveillance efforts for the detection and control of bluetongue in Kazakhstan by indicating where and when outbreaks of bluetongue are most likely to occur.

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Dynamics of swine influenza model with optimal control

Advances in Difference Equations ◽

10.1186/s13662-019-2434-4 ◽

2019 ◽

Vol 2019 (1) ◽

Author(s):

Takasar Hussain ◽

Muhammad Ozair ◽

Kazeem Oare Okosun ◽

Muhammad Ishfaq ◽

Aziz Ullah Awan ◽

...

Keyword(s):

Deterministic Model ◽

Reproduction Number ◽

Control Strategies ◽

Influenza Pandemic ◽

Swine Influenza ◽

Transmission Dynamics ◽

Model Parameters ◽

And Control ◽

Disease Free ◽

Good Agreement

AbstractTransmission dynamics of swine influenza pandemic is analysed through a deterministic model. Qualitative analysis of the model includes global asymptotic stability of disease-free and endemic equilibria under a certain condition based on the reproduction number. Sensitivity analysis to ponder the effect of model parameters on the reproduction number is performed and control strategies are designed. It is also verified that the obtained numerical results are in good agreement with the analytical ones.

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Assessing the effects of time-dependent restrictions and control actions to flatten the curve of COVID-19 in Kazakhstan

PeerJ ◽

10.7717/peerj.10806 ◽

2021 ◽

Vol 9 ◽

pp. e10806

Author(s):

Ton Duc Do ◽

Meei Mei Gui ◽

Kok Yew Ng

Keyword(s):

Ad Hoc ◽

Reproduction Number ◽

National Level ◽

Control Measures ◽

Time Dependent ◽

Transmission Dynamics ◽

Model Parameters ◽

Real World Data ◽

Control Actions ◽

And Control

This article presents the assessment of time-dependent national-level restrictions and control actions and their effects in fighting the COVID-19 pandemic. By analysing the transmission dynamics during the first wave of COVID-19 in the country, the effectiveness of the various levels of control actions taken to flatten the curve can be better quantified and understood. This in turn can help the relevant authorities to better plan for and control the subsequent waves of the pandemic. To achieve this, a deterministic population model for the pandemic is firstly developed to take into consideration the time-dependent characteristics of the model parameters, especially on the ever-evolving value of the reproduction number, which is one of the critical measures used to describe the transmission dynamics of this pandemic. The reproduction number alongside other key parameters of the model can then be estimated by fitting the model to real-world data using numerical optimisation techniques or by inducing ad-hoc control actions as recorded in the news platforms. In this article, the model is verified using a case study based on the data from the first wave of COVID-19 in the Republic of Kazakhstan. The model is fitted to provide estimates for two settings in simulations; time-invariant and time-varying (with bounded constraints) parameters. Finally, some forecasts are made using four scenarios with time-dependent control measures so as to determine which would reflect on the actual situations better.

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A Dynamic Model of Human and Livestock Tuberculosis Spread and Control in Urumqi, Xinjiang, China

Computational and Mathematical Methods in Medicine ◽

10.1155/2016/3410320 ◽

2016 ◽

Vol 2016 ◽

pp. 1-10

Author(s):

Shan Liu ◽

Aiqiao Li ◽

Xiaomei Feng ◽

Xueliang Zhang ◽

Kai Wang

Keyword(s):

Sensitivity Analysis ◽

Confidence Interval ◽

Dynamic Model ◽

Basic Reproduction Number ◽

Reproduction Number ◽

Model Parameters ◽

Epidemiological Investigation ◽

Dynamical Behaviors ◽

And Control ◽

The Basic Reproduction Number

We establish a dynamical model for tuberculosis of humans and cows. For the model, we firstly give the basic reproduction numberR0. Furthermore, we discuss the dynamical behaviors of the model. By epidemiological investigation of tuberculosis among humans and livestock from 2007 to 2014 in Urumqi, Xinjiang, China, we estimate the parameters of the model and study the transmission trend of the disease in Urumqi, Xinjiang, China. The reproduction number in Urumqi for the model is estimated to be 0.1811 (95% confidence interval: 0.123–0.281). Finally, we perform some sensitivity analysis of several model parameters and give some useful comments on controlling the transmission of tuberculosis.

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Clinical, epidemiological and climatic factors related to the occurrence of cutaneous leishmaniasis in an endemic area in northeastern Brazil

Brazilian Journal of Biology ◽

10.1590/1519-6984.224937 ◽

2020 ◽

Author(s):

R. S. Oliveira ◽

K. B. A. Pimentel ◽

M. L. Moura ◽

C. F. Aragão ◽

A. S. Guimarães-e-Silva ◽

...

Keyword(s):

Cutaneous Leishmaniasis ◽

Climatic Factors ◽

Wide Distribution ◽

Northeastern Brazil ◽

Public Health Issue ◽

Air Humidity ◽

Disease Occurrence ◽

Relative Air Humidity ◽

Age Range ◽

And Control

Abstract Cutaneous leishmaniasis (CL) is a neglected tropical disease with a wide distribution in the Americas. Brazil is an endemic country and present cases in all states. This study aimed to describe the occurrence, the underlying clinical and epidemiological factors, and the correlation of climatic variables with the frequency of reported CL cases in the municipality of Caxias, state of Maranhão, Brazil. This is a retrospective and descriptive epidemiological study based on data extracted from the Brazilian Information System of Diseases Notification, from 2007 to 2017. Maximum and minimum temperature, precipitation, and relative air humidity data were provided by the Brazilian National Institute of Meteorology. A total of 201 reported autochthonous CL cases were analyzed. The predominance of cases was observed in males (70.1%). The age range between 31 and 60 years old was the most affected, with 96 cases (47.9%). Of the total number of registered cases, 38.8% of the affected individuals were engaged in agriculture-related activities. The georeferenced distribution revealed the heterogeneity of disease occurrence, with cases concentrated in the Western and Southern regions of the municipality. An association was detected between relative air humidity (monthly mean) and the number of CL cases per month (p = 0.04). CL continues to be a concerning public health issue in Caxias. In this context, there is a pressing need to strengthen measures of prevention and control of the disease through the network of health services of the municipality, considering local and regional particularities.

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Structural comparison of CD163 SRCR5 from different species sheds some light on its involvement in porcine reproductive and respiratory syndrome virus-2 infection in vitro

Veterinary Research ◽

10.1186/s13567-021-00969-z ◽

2021 ◽

Vol 52 (1) ◽

Author(s):

Hongfang Ma ◽

Rui Li ◽

Longguang Jiang ◽

Songlin Qiao ◽

Xin-xin Chen ◽

...

Keyword(s):

Scavenger Receptor ◽

Host Cells ◽

Respiratory Syndrome Virus ◽

Swine Industry ◽

Prrs Virus ◽

Rich Domain ◽

Serious Disease ◽

The One ◽

And Control

AbstractPorcine reproductive and respiratory syndrome (PRRS) is a serious disease burdening global swine industry. Infection by its etiological agent, PRRS virus (PRRSV), shows a highly restricted tropism of host cells and has been demonstrated to be mediated by an essential scavenger receptor (SR) CD163. CD163 fifth SR cysteine-rich domain (SRCR5) is further proven to play a crucial role during viral infection. Despite intense research, the involvement of CD163 SRCR5 in PRRSV infection remains to be elucidated. In the current study, we prepared recombinant monkey CD163 (moCD163) SRCR5 and human CD163-like homolog (hCD163L1) SRCR8, and determined their crystal structures. After comparison with the previously reported crystal structure of porcine CD163 (pCD163) SRCR5, these structures showed almost identical structural folds but significantly different surface electrostatic potentials. Based on these differences, we carried out mutational research to identify that the charged residue at position 534 in association with the one at position 561 were important for PRRSV-2 infection in vitro. Altogether the current work sheds some light on CD163-mediated PRRSV-2 infection and deepens our understanding of the viral pathogenesis, which will provide clues for prevention and control of PRRS.

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Dynamics of the rumor-spreading model with hesitation mechanism in heterogenous networks and bilingual environment

Advances in Difference Equations ◽

10.1186/s13662-020-03081-2 ◽

2020 ◽

Vol 2020 (1) ◽

Author(s):

Shuai Yang ◽

Haijun Jiang ◽

Cheng Hu ◽

Juan Yu ◽

Jiarong Li

Keyword(s):

Lyapunov Method ◽

Reproduction Number ◽

Model Parameters ◽

Rumor Spreading ◽

Spreading Model ◽

Reductio Ad Absurdum ◽

The Stability ◽

The Impact ◽

Theoretical Results ◽

The Basic Reproduction Number

Abstract In this paper, a novel rumor-spreading model is proposed under bilingual environment and heterogenous networks, which considers that exposures may be converted to spreaders or stiflers at a set rate. Firstly, the nonnegativity and boundedness of the solution for rumor-spreading model are proved by reductio ad absurdum. Secondly, both the basic reproduction number and the stability of the rumor-free equilibrium are systematically discussed. Whereafter, the global stability of rumor-prevailing equilibrium is explored by utilizing Lyapunov method and LaSalle’s invariance principle. Finally, the sensitivity analysis and the numerical simulation are respectively presented to analyze the impact of model parameters and illustrate the validity of theoretical results.

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Analysis and prediction of the coronavirus disease epidemic in China based on an individual-based model

Scientific Reports ◽

10.1038/s41598-020-76969-4 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Zuiyuan Guo ◽

Dan Xiao

Keyword(s):

Reproduction Number ◽

Control Measures ◽

Cumulative Number ◽

Individual Based Model ◽

Whole Process ◽

Coordinate Descent Algorithm ◽

Initial Stage ◽

The Government ◽

Prevention And Control Measures ◽

And Control

AbstractWe established a stochastic individual-based model and simulated the whole process of occurrence, development, and control of the coronavirus disease epidemic and the infectors and patients leaving Hubei Province before the traffic was closed in China. Additionally, the basic reproduction number (R0) and number of infectors and patients who left Hubei were estimated using the coordinate descent algorithm. The median R0 at the initial stage of the epidemic was 4.97 (95% confidence interval [CI] 4.82–5.17). Before the traffic lockdown was implemented in Hubei, 2000 (95% CI 1982–2030) infectors and patients had left Hubei and traveled throughout the country. The model estimated that if the government had taken prevention and control measures 1 day later, the cumulative number of laboratory-confirmed patients in the whole country would have increased by 32.1%. If the lockdown of Hubei was imposed 1 day in advance, the cumulative number of laboratory-confirmed patients in other provinces would have decreased by 7.7%. The stochastic model could fit the officially issued data well and simulate the evolution process of the epidemic. The intervention measurements nationwide have effectively curbed the human-to-human transmission of severe acute respiratory syndrome coronavirus 2.

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Heterogeneity and effectiveness analysis of COVID-19 prevention and control in major cities in China through time-varying reproduction number estimation

Scientific Reports ◽

10.1038/s41598-020-79063-x ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Qing Cheng ◽

Zeyi Liu ◽

Guangquan Cheng ◽

Jincai Huang

Keyword(s):

Prevention And Control ◽

Large Scale ◽

Reproduction Number ◽

Correlation Method ◽

Control Measures ◽

Time Varying ◽

Short Period ◽

Significant Difference ◽

Prevention And Control Measures ◽

And Control

AbstractBeginning on December 31, 2019, the large-scale novel coronavirus disease 2019 (COVID-19) emerged in China. Tracking and analysing the heterogeneity and effectiveness of cities’ prevention and control of the COVID-19 epidemic is essential to design and adjust epidemic prevention and control measures. The number of newly confirmed cases in 25 of China’s most-affected cities for the COVID-19 epidemic from January 11 to February 10 was collected. The heterogeneity and effectiveness of these 25 cities’ prevention and control measures for COVID-19 were analysed by using an estimated time-varying reproduction number method and a serial correlation method. The results showed that the effective reproduction number (R) in 25 cities showed a downward trend overall, but there was a significant difference in the R change trends among cities, indicating that there was heterogeneity in the spread and control of COVID-19 in cities. Moreover, the COVID-19 control in 21 of 25 cities was effective, and the risk of infection decreased because their R had dropped below 1 by February 10, 2020. In contrast, the cities of Wuhan, Tianmen, Ezhou and Enshi still had difficulty effectively controlling the COVID-19 epidemic in a short period of time because their R was greater than 1.

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