scholarly journals Modeling COVID 19 in the Basque Country: from introduction to control measure response

2020 ◽  
Author(s):  
Maíra Aguiar ◽  
Eduardo Millán Ortuondo ◽  
Joseba Bidaurrazaga Van-Dierdonck ◽  
Javier Mar ◽  
Nico Stollenwerk
Keyword(s):  
Disease Transmission ◽  
Task Force ◽  
Control Measure ◽  
Disease Incidence ◽  
Basque Country ◽  
National Health System ◽  
Epidemiological Data ◽  
Model Framework ◽  
Reproduction Ratio ◽  
Incidence Data

AbstractIn March 2020, a multidisciplinary task force (so-called Basque Modelling Task Force, BMTF) was created to assist the Basque Health managers and the Basque Government during the COVID-19 responses. BMTF is a modeling team, working on different approaches, including stochastic processes, statistical methods and artificial intelligence. In this paper we describe and present the results obtained by a new stochastic SHARUCD model framework which was able to describe the disease incidence data provided by the Basque Health Services. Our models differentiate mild and asymptomatic from severe infections prone to be hospitalized and were able to predict the course of the epidemic, from introduction to control measure response, providing important projections on the national health system necessities during the increased population demand on hospital ad-missions. Short and longer-term predictions were tested with good results adjusted to the current epidemiological data, showing that the partial lockdown measures were effective and enough to slow down disease transmission in the Basque Country. The growth rate λ Is calculated from the model and from the data and the implications for the reproduction ratio r are shown. At the moment, the reproduction ratio r is estimated to be below the threshold behavior of r = 1, but still close to 1, meaning that although the number of new cases are decelerating, a careful monitoring of the development of the outbreak is required. This framework is now being used to monitor disease transmission while the country lock-down is gradually lifted, with insights to specific programs for a general policy of “social distancing” and home quarantining. These are the first publicly available modeling results for the Basque Country and the efforts will be continued taking into consideration the updated data and new information that are generated over time.

scholarly journals Modelling COVID 19 in the Basque Country from introduction to control measure response

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Maíra Aguiar ◽  
Eduardo Millán Ortuondo ◽  
Joseba Bidaurrazaga Van-Dierdonck ◽  
Javier Mar ◽  
Nico Stollenwerk
Keyword(s):  
Disease Transmission ◽  
Hospital Admissions ◽  
Task Force ◽  
Control Measure ◽  
Basque Country ◽  
Epidemiological Data ◽  
Control Measures ◽  
Model Framework ◽  
Modeling Framework ◽  
Reproduction Ratio

Abstract In March 2020, a multidisciplinary task force (so-called Basque Modelling Task Force, BMTF) was created to assist the Basque health managers and Government during the COVID-19 responses. BMTF is a modelling team, working on different approaches, including stochastic processes, statistical methods and artificial intelligence. Here we describe the efforts and challenges to develop a flexible modeling framework able to describe the dynamics observed for the tested positive cases, including the modelling development steps. The results obtained by a new stochastic SHARUCD model framework are presented. Our models differentiate mild and asymptomatic from severe infections prone to be hospitalized and were able to predict the course of the epidemic, providing important projections on the national health system’s necessities during the increased population demand on hospital admissions. Short and longer-term predictions were tested with good results adjusted to the available epidemiological data. We have shown that the partial lockdown measures were effective and enough to slow down disease transmission in the Basque Country. The growth rate $$ \lambda $$ λ was calculated from the model and from the data and the implications for the reproduction ratio r are shown. The analysis of the growth rates from the data led to improved model versions describing after the exponential phase also the new information obtained during the phase of response to the control measures. This framework is now being used to monitor disease transmission while the country lockdown was gradually lifted, with insights to specific programs for a general policy of “social distancing” and home quarantining.

scholarly journals Reproduction ratio and growth rates: measures for an unfolding pandemic

2020 ◽  
Author(s):  
Maíra Aguiar ◽  
Joseba Bidaurrazaga Van-Dierdonck ◽  
Nico Stollenwerk
Keyword(s):  
Growth Rates ◽  
Disease Transmission ◽  
Task Force ◽  
Basque Country ◽  
Recovery Period ◽  
Data Sets ◽  
Reproduction Ratio ◽  
Task Forces ◽  
Reproduction Numbers ◽  
Health Managers

AbstractThe initial exponential growth rate of an epidemic is an important measure that follows directly from data at hand, commonly used to infer the basic reproduction number. As the growth rates λ(t) of tested positive COVID-19 cases have crossed the threshold in many countries, with negative numbers as surrogate for disease transmission deceleration, lockdowns lifting are linked to the behavior of the momentary reproduction numbers r(t), often called R0. Important to note that this concept alone can be easily misinterpreted as it is bound to many internal assumptions of the underlying model and significantly affected by the assumed recovery period. Here we present our experience, as part of the Basque Country Modeling Task Force (BMTF), in monitoring the development of the COVID-19 epidemic, by considering not only the behaviour of r(t) estimated for the new tested positive cases - significantly affected by the increased testing capacities, but also the momentary growth rates for hospitalizations, ICU admissions, deceased and recovered cases, in assisting the Basque Health Managers and the Basque Government during the lockdown lifting measures. Two different data sets, collected and then refined during the COVID-19 responses, are used as an exercise to estimate the momentary growth rates and reproducetion numbers over time in the Basque Country, and the implications of using those concepts to make decisions about easing lockdown and relaxing social distancing measures are discussed. These results are potentially helpful for task forces around the globe which are now struggling to provide real scientific advice for health managers and governments while the lockdown measures are relaxed.

scholarly journals The effectiveness of full and partial travel bans against COVID-19 spread in Australia for travellers from China during and after the epidemic peak in China

2020 ◽  
Vol 27 (5) ◽  
Author(s):  
Valentina Costantino ◽  
David J Heslop ◽  
C Raina MacIntyre
Keyword(s):  
Deterministic Model ◽  
Control Measure ◽  
Disease Incidence ◽  
Policy Option ◽  
Air Travel ◽  
Incidence Data ◽  
Travel Restrictions ◽  
Imported Cases ◽  
Using Data ◽  
The Impact

Abstract Background Australia implemented a travel ban on China on 1 February 2020, while COVID-19 was largely localized to China. We modelled three scenarios to test the impact of travel bans on epidemic control. Scenario one was no ban; scenario two and three were the current ban followed by a full or partial lifting (allow over 100 000 university students to enter Australia, but not tourists) from the 8th of March 2020. Methods We used disease incidence data from China and air travel passenger movements between China and Australia during and after the epidemic peak in China, derived from incoming passenger arrival cards. We used the estimated incidence of disease in China, using data on expected proportion of under-ascertainment of cases and an age-specific deterministic model to model the epidemic in each scenario. Results The modelled epidemic with the full ban fitted the observed incidence of cases well, predicting 57 cases on March 6th in Australia, compared to 66 observed on this date; however, we did not account for imported cases from other countries. The modelled impact without a travel ban results in more than 2000 cases and about 400 deaths, if the epidemic remained localized to China and no importations from other countries occurred. The full travel ban reduced cases by about 86%, while the impact of a partial lifting of the ban is minimal and may be a policy option. Conclusions Travel restrictions were highly effective for containing the COVID-19 epidemic in Australia during the epidemic peak in China and averted a much larger epidemic at a time when COVID-19 was largely localized to China. This research demonstrates the effectiveness of travel bans applied to countries with high disease incidence. This research can inform decisions on placing or lifting travel bans as a control measure for the COVID-19 epidemic.

scholarly journals The impact of surveillance and control on highly pathogenic avian inuenza outbreaks in poultry in Dhaka division, Bangladesh

2017 ◽  
Author(s):  
Edward M. Hill ◽  
Thomas House ◽  
Madhur S. Dhingra ◽  
Wantanee Kalpravidh ◽  
Subhash Morzaria ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Control Measure ◽  
Control Policy ◽  
Transmission Model ◽  
Model Framework ◽  
Highly Pathogenic ◽  
Management Actions ◽  
H5n1 Influenza ◽  
And Control ◽  
The Impact

AbstractIn Bangladesh, the poultry industry is an economically and socially important sector, but it is persistently threatened by the effects of H5N1 highly pathogenic avian influenza. Thus, identifying the optimal control policy in response to an emerging disease outbreak is a key challenge for policy-makers. To inform this aim, a common approach is to carry out simulation studies comparing plausible strategies, while accounting for known capacity restrictions. In this study we perform simulations of a previously developed H5N1 influenza transmission model framework, fitted to two separate historical outbreaks, to assess specific control objectives related to the burden or duration of H5N1 outbreaks among poultry farms in the Dhaka division of Bangladesh. In particular, we explore the optimal implementation of ring culling, ring vaccination and active surveillance measures when presuming disease transmission predominately occurs from premises-to-premises, versus a setting requiring the inclusion of external factors. Additionally, we determine the sensitivity of the management actions under consideration to differing levels of capacity constraints and outbreaks with disparate transmission dynamics. While we find that reactive culling and vaccination policies should pay close attention to these factors to ensure intervention targeting is optimised, across multiple settings the top performing control action amongst those under consideration were targeted proactive surveillance schemes. Our findings may advise the type of control measure, plus its intensity, that could potentially be applied in the event of a developing outbreak of H5N1 amongst originally H5N1 virus-free commercially-reared poultry in the Dhaka division of Bangladesh.

scholarly journals The effectiveness of full and partial travel bans against COVID-19 spread in Australia for travellers from China

2020 ◽  
Author(s):  
Valentina Costantino ◽  
David Heslop ◽  
Raina Macintyre
Keyword(s):  
Deterministic Model ◽  
Control Measure ◽  
Disease Incidence ◽  
Policy Option ◽  
True Incidence ◽  
Incidence Data ◽  
Travel Restrictions ◽  
Imported Cases ◽  
Using Data ◽  
The Impact

Abstract Background: Australia implemented a travel ban on China on February 1st 2020. Partial lifting of the ban is being considered, given the decline in incidence of COVID-19 in China. We modelled three scenarios to test the impact of travel bans on epidemic control in Australia. Scenario one was no ban, scenario two and three were the current ban followed by a full and partial lifting from the 8th of March 2020.Methods: We used disease incidence data from China and air travel passenger movements between China and Australia, derived from incoming passenger arrival cards. We estimated the true incidence of disease in China using data on expected proportion of under-ascertainment of cases. We modelled the epidemic in each scenario using an age specific deterministic model.Results: The modelled epidemic with the ban implementation fitted the observed incidence of cases well, predicting 57 cases on March 6th in Australia, compared to 66 observed on this date, however we did not account for imported cases from other countries. The modelled epidemic, without a travel ban implemented, would continue for more than a year resulting in more than 2000 cases and about 400 deaths. The impact of a partial lifting of a ban is minimal, and may be a policy option.Conclusions: Travel restrictions were highly effective for containing the COVID-19 epidemic in Australia and averted a much larger epidemic. This research can inform decisions on placing or lifting travel bans as a control measure for the COVID-19 epidemic.

scholarly journals The effectiveness of full and partial travel bans against COVID-19 spread in Australia for travellers from China

2020 ◽  
Author(s):  
Valentina Costantino ◽  
David J Heslop ◽  
C Raina MacIntyre
Keyword(s):  
Deterministic Model ◽  
Control Measure ◽  
Disease Incidence ◽  
Policy Option ◽  
True Incidence ◽  
Incidence Data ◽  
Travel Restrictions ◽  
Imported Cases ◽  
Using Data ◽  
The Impact

AbstractAustralia implemented a travel ban on China on February 1st 2020. Partial lifting of the ban is being considered, given the decline in incidence of COVID-19 in China. We modelled three scenarios to test the impact of travel bans on epidemic control in Australia. Scenario one was no ban, scenario two was the current ban followed by a full lifting from the 8th of March 2020, scenario three was a partial lifting of the current ban to allow over 100,000 university students to enter Australia, but not tourists. We used disease incidence data from China and air travel passenger movements between China and Australia, derived from incoming passenger arrival cards. We estimated the true incidence of disease in China using data on expected proportion of under-ascertainment of cases. We used an age specific deterministic model divided in 18 age stratified groups to model the epidemic in each scenario. The modelled epidemic with the full ban fitted the observed incidence of cases well. The modelled epidemic of the current ban predicts 57 cases on March 6th in Australia, compared to 66 observed on this date, however we did not account for imported cases from other countries. The modelled impact without a travel ban implemented on February the 1st shows the epidemic would continue for more than a year resulting in more than 2000 cases and about 400 deaths. The impact of a partial lifting of a ban is minimal, and may be a policy option. Travel restrictions were highly effective for containing the COVID-19 epidemic in Australia and averted a much larger epidemic. The epidemic is still containable if other measures are used in tandem as cases surge in other countries. This research can inform decisions on placing or lifting travel bans as a control measure for the COVID-19 epidemic.

scholarly journals Stability analysis of a dynamical model of tuberculosis with incomplete treatment

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Ihsan Ullah ◽  
Saeed Ahmad ◽  
Qasem Al-Mdallal ◽  
Zareen A. Khan ◽  
Hasib Khan ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Contact Rate ◽  
Asymptotically Stable ◽  
Treatment Rate ◽  
Globally Asymptotically Stable ◽  
Reproduction Ratio ◽  
Efficient Treatment ◽  
Effective Contact ◽  
The Impact ◽  
Incomplete Treatment

Abstract A simple deterministic epidemic model for tuberculosis is addressed in this article. The impact of effective contact rate, treatment rate, and incomplete treatment versus efficient treatment is investigated. We also analyze the asymptotic behavior, spread, and possible eradication of the TB infection. It is observed that the disease transmission dynamics is characterized by the basic reproduction ratio $\Re _{0}$ ℜ 0 ; if $\Re _{0}<1$ ℜ 0 < 1 , there is only a disease-free equilibrium which is both locally and globally asymptotically stable. Moreover, for $\Re _{0}>1$ ℜ 0 > 1 , a unique positive endemic equilibrium exists which is globally asymptotically stable. The global stability of the equilibria is shown via Lyapunov function. It is also obtained that incomplete treatment of TB causes increase in disease infection while efficient treatment results in a reduction in TB. Finally, for the estimated parameters, some numerical simulations are performed to verify the analytical results. These numerical results indicate that decrease in the effective contact rate λ and increase in the treatment rate γ play a significant role in the TB infection control.

scholarly journals Pneumococcal Pneumonia and Invasive Pneumococcal Disease in Those 65 and Older: Rates of Detection, Risk Factors, Vaccine Effectiveness, Hospitalisation and Mortality

Geriatrics ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 13
Author(s):  
Roger E. Thomas
Keyword(s):  
Risk Factors ◽  
Nursing Home ◽  
Invasive Pneumococcal Disease ◽  
Disease Transmission ◽  
Pneumococcal Disease ◽  
Pneumococcal Pneumonia ◽  
Clinical Symptoms ◽  
Disease Incidence ◽  
Family Members ◽  
Vaccination Rates

Pneumococcal pneumonia (PP) and invasive pneumococcal disease (IPD) are important causes of morbidity and mortality in seniors worldwide. Incidence rates and serious outcomes worsen with increasing frailty, numbers of risk factors and decreasing immune competence with increasing age. Literature reviews in Medline and Embase were performed for pneumococcal disease incidence, risk factors, vaccination rates and effectiveness in the elderly. The introduction of protein-conjugated pneumoccal vaccines (PCV) for children markedly reduced IPD and PP in seniors, but serotypes not included in vaccines and with previously low levels increased. Pneumococcal polysaccharide (PPV23) vaccination does not change nasal and pharyngeal carriage rates. Pneumococcal and influenza vaccination rates in seniors are below guideline levels, especially in older seniors and nursing home staff. Pneumococcal and influenza carriage and vaccination rates of family members, nursing home health care workers and other contacts are unknown. National vaccination programmes are effective in increasing vaccination rates. Detection of IPD and PP initially depend on clinical symptoms and new chest X ray infiltrates and then varies according to the population and laboratory tests used. To understand how seniors and especially older seniors acquire PP and IPD data are needed on pneumococcal disease and carriage rates in family members, carers and contacts. Nursing homes need reconfiguring into small units with air ventilation externally from all rooms to minimise respiratory disease transmission and dedicated staff for each unit to minimise transmision of infectious diseaases.

scholarly journals Using Commercial Compost as Control Measures against Cucumber Root-Rot Disease

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Kamel Kamal Sabet ◽  
Magdy Mohamed Saber ◽  
Mohamed Adel-Aziz El-Naggar ◽  
Nehal Samy El-Mougy ◽  
Hatem Mohamed El-Deeb ◽  
...  
Keyword(s):  
Root Rot ◽  
Control Measure ◽  
Disease Incidence ◽  
Pathogenic Fungi ◽  
Pythium Ultimum ◽  
Control Measures ◽  
Infested Soil ◽  
Fungal Isolates ◽  
Cucumber Root

Five commercial composts were evaluated to suppress the root-rot pathogens (Fusarium solani (Mart.) App. and Wr, Pythium ultimum Trow, Rhizoctonia solani Kuhn, and Sclerotium rolfsii Sacc.) of cucumber plants under in vitro and greenhouse conditions. In vitro tests showed that all tested unautoclaved and unfiltrated composts water extracts (CWEs) had inhibitor effect against pathogenic fungi, compared to autoclaved and filtrated ones. Also, the inhibitor effects of 40 bacteria and 15 fungi isolated from composts were tested against the mycelial growth of cucumber root-rot pathogens. Twenty two bacteria and twelve fungal isolates had antagonistic effect against root-rot pathogens. The antagonistic fungal isolates were identified as 6 isolates belong to the genus Aspergillus spp., 5 isolates belong to the genus Penicillium spp. and one isolate belong to the genus Chaetomium spp. Under greenhouse conditions, the obtained results in pot experiment using artificial infested soil with cucumber root-rot pathogens showed that the compost amended soil reduced the percentage of disease incidence, pathogenic fungi population, and improved the cucumber vegetative parameters as shoot length, root length, fresh weight, and dry weight. These results suggested that composts are consequently considered as control measure against cucumber root-rot pathogens.

scholarly journals Modeling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil

2021 ◽  
Author(s):  
Marcelo Eduardo Borges ◽  
Leonardo Souto Ferreira ◽  
Silas Poloni ◽  
Ângela Maria Bagattini ◽  
Caroline Franco ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Transmission Rate ◽  
Disease Incidence ◽  
Demographic Data ◽  
School Closure ◽  
Mitigation Measures ◽  
Contact Tracing ◽  
School Closures ◽  
Infection Transmission ◽  
The Impact

Among the various non–pharmaceutical interventions implemented in response to the Covid–19 pandemic during 2020, school closures have been in place in several countries to reduce infection transmission. Nonetheless, the significant short and long–term impacts of prolonged suspension of in–person classes is a major concern. There is still considerable debate around the best timing for school closure and reopening, its impact on the dynamics of disease transmission, and its effectiveness when considered in association with other mitigation measures. Despite the erratic implementation of mitigation measures in Brazil, school closures were among the first measures taken early in the pandemic in most of the 27 states in the country. Further, Brazil delayed the reopening of schools and stands among the countries in which schools remained closed for the most prolonged period in 2020. To assess the impact of school reopening and the effect of contact tracing strategies in rates of Covid–19 cases and deaths, we model the epidemiological dynamics of disease transmission in 3 large urban centers in Brazil under different epidemiological contexts. We implement an extended SEIR model stratified by age and considering contact networks in different settings – school, home, work, and elsewhere, in which the infection transmission rate is affected by various intervention measures. After fitting epidemiological and demographic data, we simulate scenarios with increasing school transmission due to school reopening. Our model shows that reopening schools results in a non–linear increase of reported Covid-19 cases and deaths, which is highly dependent on infection and disease incidence at the time of reopening. While low rates of within[&ndash]school transmission resulted in small effects on disease incidence (cases/100,000 pop), intermediate or high rates can severely impact disease trends resulting in escalating rates of new cases even if other interventions remain unchanged. When contact tracing and quarantining are restricted to school and home settings, a large number of daily tests is required to produce significant effects of reducing the total number of hospitalizations and deaths. Our results suggest that policymakers should carefully consider the epidemiological context and timing regarding the implementation of school closure and return of in-person school activities. Also, although contact tracing strategies are essential to prevent new infections and outbreaks within school environments, our data suggest that they are alone not sufficient to avoid significant impacts on community transmission in the context of school reopening in settings with high and sustained transmission rates.

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