Transmission dynamics and successful control measures of SARS-CoV-2 in the mega-size city of Guangzhou, China

AbstractThe problem of foot and mouth disease (FMD) is of serious concern to the livestock sector in most nations, especially in developing countries. This paper presents the formulation and analysis of a deterministic model for the transmission dynamics of FMD through a contaminated environment. It is shown that the key parameters that drive the transmission of FMD in a contaminated environment are the shedding, transmission, and decay rates of the virus. Using numerical results, it is depicted that the host-to-host route is more severe than the environmental-to-host route. The model is then transformed into an optimal control problem. Using the Pontryagin’s Maximum Principle, the optimality system is determined. Utilizing a gradient type algorithm with projection, the optimality system is solved for three control strategies: optimal use of vaccination, environmental decontamination, and a combination of vaccination and environmental decontamination. Results show that a combination of vaccination and environmental decontamination is the most optimal strategy. These results indicate that if vaccination and environmental decontamination are used optimally during an outbreak, then FMD transmission can be controlled. Future studies focusing on the control measures for the transmission of FMD in a contaminated environment should aim at reducing the transmission and the shedding rates, while increasing the decay rate.

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Lantana camara (lantana).

10.1079/cpc.29771.20210100317 ◽

2021 ◽

Author(s):

Sarah E. Thomas ◽

Julissa Rojas-Sandoval ◽

Pedro Acevedo-Rodríguez

Keyword(s):

South Africa ◽

Biological Control ◽

Control Measures ◽

Economic Losses ◽

Pests And Diseases ◽

Control Programmes ◽

Agricultural Weed ◽

Successful Control ◽

The Tropics ◽

Ornamental Shrub

Abstract L. camara is a highly variable ornamental shrub, native of the neotropics. It has been introduced to most of the tropics and subtropics as a hedge plant and has since been reported as extremely weedy and invasive in many countries. It is generally deleterious to biodiversity and has been reported as an agricultural weed resulting in large economic losses in a number of countries. In addition to this, it increases the risk of fire, is poisonous to livestock and is a host for numerous pests and diseases. L. camara is difficult to control. In Australia, India and South Africa aggressive measures to eradicate L. camara over the last two centuries have been largely unsuccessful, and the invasion trajectory has continued upwards despite control measures. This species has been the target of biological control programmes for over a century, with successful control only being reported in a few instances.

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Modeling the Novel Coronavirus (SARS-CoV-2) Outbreak in Sicily, Italy

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17144964 ◽

2020 ◽

Vol 17 (14) ◽

pp. 4964 ◽

Cited By ~ 5

Author(s):

Andrea Maugeri ◽

Martina Barchitta ◽

Sebastiano Battiato ◽

Antonella Agodi

Keyword(s):

Transmission Rate ◽

Control Measures ◽

Transmission Dynamics ◽

The Novel ◽

Epidemic Spread ◽

Transmission Rates ◽

Contact Precautions ◽

Travel Restrictions ◽

Novel Coronavirus ◽

Reported Data

Italy was the first country in Europe which imposed control measures of travel restrictions, quarantine and contact precautions to tackle the epidemic spread of the novel coronavirus (SARS-CoV-2) in all its regions. While such efforts are still ongoing, uncertainties regarding SARS-CoV-2 transmissibility and ascertainment of cases make it difficult to evaluate the effectiveness of restrictions. Here, we employed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model to assess SARS-CoV-2 transmission dynamics, working on the number of reported patients in intensive care unit (ICU) and deaths in Sicily (Italy), from 24 February to 13 April. Overall, we obtained a good fit between estimated and reported data, with a fraction of unreported SARS-CoV-2 cases (18.4%; 95%CI = 0–34.0%) before 10 March lockdown. Interestingly, we estimated that transmission rate in the community was reduced by 32% (95%CI = 23–42%) after the first set of restrictions, and by 80% (95%CI = 70–89%) after those adopted on 23 March. Thus, our estimates delineated the characteristics of SARS-CoV2 epidemic before restrictions taking into account unreported data. Moreover, our findings suggested that transmission rates were reduced after the adoption of control measures. However, we cannot evaluate whether part of this reduction might be attributable to other unmeasured factors, and hence further research and more accurate data are needed to understand the extent to which restrictions contributed to the epidemic control.

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Integrating serological and genetic data to quantify cross-species transmission: brucellosis as a case study

Parasitology ◽

10.1017/s0031182016000044 ◽

2016 ◽

Vol 143 (7) ◽

pp. 821-834 ◽

Cited By ~ 15

Author(s):

MAFALDA VIANA ◽

GABRIEL M. SHIRIMA ◽

KUNDA S. JOHN ◽

JULIE FITZPATRICK ◽

RUDOVICK R. KAZWALA ◽

...

Keyword(s):

Process Model ◽

Epidemiological Data ◽

Human Infection ◽

Control Measures ◽

Transmission Dynamics ◽

Northern Tanzania ◽

Animal Infection ◽

Latent Process ◽

Level Of Understanding

SUMMARYEpidemiological data are often fragmented, partial, and/or ambiguous and unable to yield the desired level of understanding of infectious disease dynamics to adequately inform control measures. Here, we show how the information contained in widely available serology data can be enhanced by integration with less common type-specific data, to improve the understanding of the transmission dynamics of complex multi-species pathogens and host communities. Using brucellosis in northern Tanzania as a case study, we developed a latent process model based on serology data obtained from the field, to reconstruct Brucella transmission dynamics. We were able to identify sheep and goats as a more likely source of human and animal infection than cattle; however, the highly cross-reactive nature of Brucella spp. meant that it was not possible to determine which Brucella species (B. abortus or B. melitensis) is responsible for human infection. We extended our model to integrate simulated serology and typing data, and show that although serology alone can identify the host source of human infection under certain restrictive conditions, the integration of even small amounts (5%) of typing data can improve understanding of complex epidemiological dynamics. We show that data integration will often be essential when more than one pathogen is present and when the distinction between exposed and infectious individuals is not clear from serology data. With increasing epidemiological complexity, serology data become less informative. However, we show how this weakness can be mitigated by integrating such data with typing data, thereby enhancing the inference from these data and improving understanding of the underlying dynamics.

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A STUDY OF SCHISTOSOME TRANSMISSION DYNAMICS AND ITS CONTROL

Journal of Biological System ◽

10.1142/s0218339006001799 ◽

2006 ◽

Vol 14 (02) ◽

pp. 295-302 ◽

Cited By ~ 2

Author(s):

PRASENJIT DAS ◽

DEBASIS MUKHERJEE ◽

A. K. SARKAR

Keyword(s):

Numerical Simulations ◽

Mathematical Analysis ◽

Control Measure ◽

Model Analysis ◽

Unstable Equilibrium ◽

Control Measures ◽

Transmission Dynamics ◽

Delay Effect

This article concentrates on the study of delay effect on a model of schistosomiasis transmission with control measures such as predation or harvesting and chemotherapy. In the presence of predation or harvesting and chemotherapy, system admits multiple endemic equilibria. Mathematical analysis shows that they are opposite in nature regarding stability. One may observe switching phenomena for the unstable equilibrium by incorporating delay. The disease may be highly endemic if there is no control measure, which is obvious from the model analysis. Results obtained in this paper are also verified through numerical simulations.

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Lumpy skin disease in southern Africa : a review of the disease and aspects of control

Journal of the South African Veterinary Association ◽

10.4102/jsava.v72i2.619 ◽

2001 ◽

Vol 72 (2) ◽

Cited By ~ 42

Author(s):

P. Hunter ◽

D. Wallace

Keyword(s):

South Africa ◽

Southern Africa ◽

Skin Disease ◽

Control Measures ◽

Lumpy Skin Disease ◽

Strain Vaccine ◽

Successful Control

This article reviews some of the important aspects of lumpy skin disease (LSD) that may impact on its successful control. A resurgence of the disease in the last decade has highlighted some constraints of the Neethling strain vaccine, but there is no evidence of vaccine breakdowns owing to the presence of heterologous field strains. More research is needed on epidemiology and transmission of LSD in South Africa to formulate control measures.

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Successful Control of Hepatitis B Surface Antigenemia in a Dialysis Unit Without Geographic or Machine Isolation

Infection Control ◽

10.1017/s0195941700053868 ◽

1981 ◽

Vol 2 (2) ◽

pp. 101-104

Author(s):

Victor S. Ostrower ◽

Meyer D. Lifschitz ◽

Philip C. Craven ◽

Dwight M. Williams

Keyword(s):

Hepatitis B ◽

Parallel Plate ◽

Control Measures ◽

Temporal Isolation ◽

Dialysis Unit ◽

Hbsag Positivity ◽

Successful Control ◽

Prospective Trials ◽

The Mean ◽

Geographic Separation

AbstractPersistent hepatitis B infections among patients and frequent new hepatitis B infections among both patients and staff were a major problem in our dialysis unit during its first two and one-half years of operation. During this time the mean quarterly rate of conversion to HBsAg positivity among patients ranged from 0-60% (mean 12%); in staff it ranged from 0-13%. Control efforts, including strict temporal isolation, improved sanitary measures, and use of parallel plate dialyzers without geographic or machine isolation, were begun late in 1976. After a four-month lag, new HBsAg conversions ceased among the 30 patients and staff at risk, despite continued dialysis of eight HBsAg-positive patients (at least four of whom were HBeAg-positive). Over the succeeding three years the conversion rate was zero in both patients and staff. This experience suggests that conservative control measures without geographic separation of patients may be sufficient to control an established outbreak of hemodi-alysis-related hepatitis B. Controlled prospective trials of this hypothesis are warranted.

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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

10.21203/rs.3.rs-31349/v1 ◽

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.

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Transmission dynamics, serial interval and epidemiology of COVID-19 diseases in Hong Kong under different control measures

Wellcome Open Research ◽

10.12688/wellcomeopenres.15896.2 ◽

2020 ◽

Vol 5 ◽

pp. 91

Author(s):

Yung-Wai Desmond Chan ◽

Stefan Flasche ◽

Tin-Long Terence Lam ◽

Mei-Hung Joanna Leung ◽

Miu-Ling Wong ◽

...

Keyword(s):

Hong Kong ◽

Population Level ◽

Credible Interval ◽

Control Measures ◽

Transmission Dynamics ◽

Local Data ◽

First Case ◽

Serial Interval ◽

Imported Cases ◽

Epidemiological Characteristics

Background: The outbreak of coronavirus disease 2019 (COVID-19) started in Wuhan, China in late December 2019, and subsequently became a pandemic. Hong Kong had implemented a series of control measures since January 2020, including enhanced surveillance, isolation and quarantine, border control and social distancing. Hong Kong recorded its first case on 23 January 2020, who was a visitor from Wuhan. We analysed the surveillance data of COVID-19 to understand the transmission dynamics and epidemiology in Hong Kong. Methods: We constructed the epidemic curve of daily COVID-19 incidence from 23 January to 6 April 2020 and estimated the time-varying reproduction number (Rt) with the R package EpiEstim, with serial interval computed from local data. We described the demographic and epidemiological characteristics of reported cases. We computed weekly incidence by age and residential district to understand the spatial and temporal transmission of the disease. Results: COVID-19 disease in Hong Kong was characterised with local cases and clusters detected after two waves of importations, first in late January (week 4 to 6) and the second one in early March (week 9 to 10). The Rt increased to approximately 2 95% credible interval (CI): 0.3-3.3) and approximately 1 (95%CI: 0.2-1.7), respectively, following these importations; it decreased to below 1 afterwards from weeks 11 to 13, which coincided with the implementation, modification and intensification of different control measures. Compared to local cases, imported cases were younger (mean age: 52 years among local cases vs 35 years among imported cases), had a lower proportion of underlying disease (9% vs 5%) and severe outcome (13% vs 5%). Cases were recorded in all districts but the incidence was highest in those in the Hong Kong Island region. Conclusions: Stringent and sustained public health measures at population level could contain the COVID-19 disease at a relatively low level.

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Model-free estimation of COVID-19 transmission dynamics from a complete outbreak

PLoS ONE ◽

10.1371/journal.pone.0238800 ◽

2021 ◽

Vol 16 (3) ◽

pp. e0238800

Author(s):

Alex James ◽

Michael J. Plank ◽

Shaun Hendy ◽

Rachelle N. Binny ◽

Audrey Lustig ◽

...

Keyword(s):

The Elderly ◽

Control Measures ◽

Transmission Dynamics ◽

Lower Probability ◽

Epidemic Dynamics ◽

Model Free ◽

Construction Techniques ◽

Imported Cases ◽

Border Controls ◽

Case Data

New Zealand had 1499 cases of COVID-19 before eliminating transmission of the virus. Extensive contract tracing during the outbreak has resulted in a dataset of epidemiologically linked cases. This data contains useful information about the transmission dynamics of the virus, its dependence on factors such as age, and its response to different control measures. We use Monte-Carlo network construction techniques to provide an estimate of the number of secondary cases for every individual infected during the outbreak. We then apply standard statistical techniques to quantify differences between groups of individuals. Children under 10 years old are significantly under-represented in the case data. Children infected fewer people on average and had a lower probability of transmitting the disease in comparison to adults and the elderly. Imported cases infected fewer people on average and also had a lower probability of transmitting than domestically acquired cases. Superspreading is a significant contributor to the epidemic dynamics, with 20% of cases among adults responsible for 65–85% of transmission. Subclinical cases infected fewer individuals than clinical cases. After controlling for outliers serial intervals were approximated with a normal distribution (μ = 4.4 days, σ = 4.7 days). Border controls and strong social distancing measures, particularly when targeted at superspreading, play a significant role in reducing the spread of COVID-19.

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