A Probabilistic Transmission Model to Assess Infection Risk from Mycobacterium Tuberculosis in Commercial Passenger Trains

African swine fever first broke out in mainland China in August 2018 and has caused a substantial loss to China’s pig industry. Numerous investigations have confirmed that trades and movements of infected pigs and pork products, feeding pigs with contaminative swills, employees, and vehicles carrying the virus are the main transmission routes of the African swine fever virus (ASFV) in mainland China. However, which transmission route is more risky and what is the specific transmission map are still not clear enough. In this study, we crawl the data related to pig farms and slaughterhouses from Baidu Map by writing the Python language and then construct the pig transport network. Following this, we establish an ASFV transmission model over the network based on probabilistic discrete-time Markov chains. Furthermore, we propose spatiotemporal backward detection and forward transmission algorithms in semi-directed weighted networks. Through the simulation and calculation, the risk of transmission routes is analyzed, and the results reveal that the infection risk for employees and vehicles with the virus is the highest, followed by contaminative swills, and the transportation of pigs and pork products is the lowest; the most likely transmission map is deduced, and it is found that ASFV spreads from northeast China to southwest China and then to west; in addition, the infection risk in each province at different times is assessed, which can provide effective suggestions for the prevention and control of ASFV.

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Household Transmission of SARS-COV-2: Insights from a Population-based Serological Survey

10.1101/2020.11.04.20225573 ◽

2020 ◽

Cited By ~ 2

Author(s):

Qifang Bi ◽

Justin Lessler ◽

Isabella Eckerle ◽

Stephen A Lauer ◽

Laurent Kaiser ◽

...

Keyword(s):

Population Based ◽

Infection Risk ◽

Household Member ◽

Transmission Model ◽

Risk Of Infection ◽

Household Transmission ◽

Working Age ◽

Community Transmission ◽

Household Members ◽

Asymptomatic Infections

AbstractImportanceKnowing the transmissibility of asymptomatic infections and risk of infection from household and community exposures is critical to SARS-CoV-2 control. Limited previous evidence is based primarily on virologic testing, which disproportionately misses mild and asymptomatic infections. Serologic measures are more likely to capture all previously infected individuals.ObjectiveEstimate the risk of SARS-CoV-2 infection from household and community exposures, and identify key risk factors for transmission and infection.DesignHousehold serosurvey and transmission model.SettingPopulation-based serosurvey in Geneva, SwitzerlandParticipants4,524 household members five years and older from 2,267 households enrolled April-June 2020.ExposuresSARS-CoV-2 infected (seropositive) household members and background risk of community transmission.Main outcomes and measuresPast SARS-CoV-2 infection confirmed through anti-SARS-CoV-2 IgG antibodies by ELISA. Chain-binomial models based on the number of infections within households were used to estimate extra-household infection risk by demographics and reported extra-household contacts, and infection risk from exposure to an infected household member by demographics and infector’s symptoms. Infections attributable to exposure to different types of infectious individuals were estimated.ResultsThe chance of being infected by a single SARS-CoV-2 infected household member was 17.2% (95%CrI 13.6-21.5%) compared to a cumulative extra-household infection risk of 5.1% (95%CrI 4.5-5.8%). Infection risk from an infected household member increased with age, from 7.5% (95%CrI 1.3-20.3%) among 5-9 years to 30.2% (95%CrI 14.3-48.2%) among those ≥65 years. Working-age adults (20-49 years) had the highest extra-household infection risk. Seropositive household members not reporting symptoms had 74.8% lower odds (95%CrI 43.8-90.3%) of infecting another household member compared to those reporting symptoms, accounting for 19.6% (95%CrI 12.9-24.5%) of all household infections.Conclusions and RelevanceThe risk of infection from exposure to a single infected household member was four-times that of extra-household exposures over the first wave of the pandemic. Young children had a lower risk from infection from household members. Asymptomatic infections are far less likely to transmit than symptomatic ones but do cause infections. While the small households in Geneva limit the contribution of household spread, household transmission likely plays a greater role in other settings.

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SARS-CoV-2 infection risk during delivery of childhood vaccination campaigns: a modelling study

10.1101/2021.05.14.21257215 ◽

2021 ◽

Author(s):

Simon R Procter ◽

Kaja R Abbas ◽

Stefan Flasche ◽

Ulla Griffiths ◽

Brittany Hagedorn ◽

...

Keyword(s):

Risk Mitigation ◽

Infection Risk ◽

Childhood Vaccination ◽

World Health ◽

Mitigation Measures ◽

Transmission Model ◽

Contact Patterns ◽

Health Organization ◽

Vaccination Campaigns ◽

N95 Respirators

Background The COVID-19 pandemic has disrupted delivery of immunisation services globally. Many countries have postponed vaccination campaigns out of concern about infection risks to staff delivering vaccination, the children being vaccinated and their families. The World Health Organization recommends considering both the benefit of preventive campaigns and the risk of SARS-CoV-2 transmission when making decisions about campaigns during COVID-19 outbreaks, but there has been little quantification of the risks. Methods We modelled excess SARS-CoV-2 infection risk to vaccinators, vaccinees and their caregivers resulting from vaccination campaigns delivered during a COVID-19 epidemic. Our model used population age-structure and contact patterns from three exemplar countries (Burkina Faso, Ethiopia, and Chile). It combined an existing compartmental transmission model of an underlying COVID-19 epidemic with a Reed-Frost model of SARS-CoV-2 infection risk to vaccinators and vaccinees. We explored how excess risk depends on key parameters governing SARS-CoV-2 transmissibility, and aspects of campaign delivery such as campaign duration, number of vaccinations, and effectiveness of personal protective equipment (PPE) and symptomatic screening. Results Infection risks differ considerably depending on the circumstances in which vaccination campaigns are conducted. A campaign conducted at the peak of a SARS-CoV-2 epidemic with high prevalence and without special infection mitigation measures could increase absolute infection risk by 32% to 58% for vaccinators, and 0.3% to 0.9% for vaccinees and caregivers. However, these risks could be reduced to 3.6% to 8.0% and 0.1% to 0.4% respectively by use of PPE that reduces transmission by 90% (as might be achieved with N95 respirators or high-quality surgical masks) and symptomatic screening. Conclusions SARS-CoV-2 infection risks to vaccinators, vaccinees and caregivers during vaccination campaigns can be greatly reduced by adequate PPE, symptomatic screening, and appropriate campaign timing. Our results support the use of adequate risk mitigation measures for vaccination campaigns held during SARS-CoV-2 epidemics, rather than cancelling them entirely.

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SARS-CoV-2 infection risk during delivery of childhood vaccination campaigns: a modelling study

BMC Medicine ◽

10.1186/s12916-021-02072-8 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Simon R. Procter ◽

Kaja Abbas ◽

Stefan Flasche ◽

Ulla Griffiths ◽

Brittany Hagedorn ◽

...

Keyword(s):

Risk Mitigation ◽

Infection Risk ◽

Childhood Vaccination ◽

World Health ◽

Mitigation Measures ◽

Transmission Model ◽

Contact Patterns ◽

Health Organization ◽

Vaccination Campaigns ◽

N95 Respirators

Abstract Background The COVID-19 pandemic has disrupted the delivery of immunisation services globally. Many countries have postponed vaccination campaigns out of concern about infection risks to the staff delivering vaccination, the children being vaccinated, and their families. The World Health Organization recommends considering both the benefit of preventive campaigns and the risk of SARS-CoV-2 transmission when making decisions about campaigns during COVID-19 outbreaks, but there has been little quantification of the risks. Methods We modelled excess SARS-CoV-2 infection risk to vaccinators, vaccinees, and their caregivers resulting from vaccination campaigns delivered during a COVID-19 epidemic. Our model used population age structure and contact patterns from three exemplar countries (Burkina Faso, Ethiopia, and Brazil). It combined an existing compartmental transmission model of an underlying COVID-19 epidemic with a Reed-Frost model of SARS-CoV-2 infection risk to vaccinators and vaccinees. We explored how excess risk depends on key parameters governing SARS-CoV-2 transmissibility, and aspects of campaign delivery such as campaign duration, number of vaccinations, and effectiveness of personal protective equipment (PPE) and symptomatic screening. Results Infection risks differ considerably depending on the circumstances in which vaccination campaigns are conducted. A campaign conducted at the peak of a SARS-CoV-2 epidemic with high prevalence and without special infection mitigation measures could increase absolute infection risk by 32 to 45% for vaccinators and 0.3 to 0.5% for vaccinees and caregivers. However, these risks could be reduced to 3.6 to 5.3% and 0.1 to 0.2% respectively by use of PPE that reduces transmission by 90% (as might be achieved with N95 respirators or high-quality surgical masks) and symptomatic screening. Conclusions SARS-CoV-2 infection risks to vaccinators, vaccinees, and caregivers during vaccination campaigns can be greatly reduced by adequate PPE, symptomatic screening, and appropriate campaign timing. Our results support the use of adequate risk mitigation measures for vaccination campaigns held during SARS-CoV-2 epidemics, rather than cancelling them entirely.

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Data-driven model for the assessment of Mycobacterium tuberculosis transmission in evolving demographic structures

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1720606115 ◽

2018 ◽

Vol 115 (14) ◽

pp. E3238-E3245 ◽

Cited By ~ 9

Author(s):

Sergio Arregui ◽

María José Iglesias ◽

Sofía Samper ◽

Dessislava Marinova ◽

Carlos Martin ◽

...

Keyword(s):

Mycobacterium Tuberculosis ◽

Data Driven ◽

Transmission Model ◽

Complex Relationship ◽

Disease Epidemiology ◽

Tuberculosis Transmission ◽

Demographic Dynamics ◽

The World ◽

Contact Data ◽

Country Specific

In the case of tuberculosis (TB), the capabilities of epidemic models to produce quantitatively robust forecasts are limited by multiple hindrances. Among these, understanding the complex relationship between disease epidemiology and populations’ age structure has been highlighted as one of the most relevant. TB dynamics depends on age in multiple ways, some of which are traditionally simplified in the literature. That is the case of the heterogeneities in contact intensity among different age strata that are common to all airborne diseases, but still typically neglected in the TB case. Furthermore, while demographic structures of many countries are rapidly aging, demographic dynamics are pervasively ignored when modeling TB spreading. In this work, we present a TB transmission model that incorporates country-specific demographic prospects and empirical contact data around a data-driven description of TB dynamics. Using our model, we find that the inclusion of demographic dynamics is followed by an increase in the burden levels predicted for the next decades in the areas of the world that are most hit by the disease today. Similarly, we show that considering realistic patterns of contacts among individuals in different age strata reshapes the transmission patterns reproduced by the models, a result with potential implications for the design of age-focused epidemiological interventions.

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