Using a Mathematical Model to Evaluate the Efficacy of TB Control Measures

Gammaitoni, Loretta; Nucci, M. C.

doi:10.3201/eid0303.970310

Cited by 206 publications

(257 citation statements)

References 22 publications

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“…Thus, any measures that will reduce either the respiratory contact with infection per susceptible or the probability that the contact leads to infection will help check the spread of the disease. Hence, this also confirms the findings of Gammaitoni and Nucci [3] which asserts that administrative control measures are the most effective since they are capable of reducing the disease incidence transmission rate to as close as possible to zero.…”

Section: Resultssupporting

confidence: 87%

“…In a related research work by Gammaitoni and Nucci [3] , where mathematical model was used to evaluate the efficacy of TB control measures, it was found that environmental control cannot eliminate the risk of TB transmission during high-risk procedures; respiratory protective devices, and particularly highefficiency particulate air masks may provide nearly complete protection if used with air filtration or ultraviolent irradiation, although the efficiency of these control measures decreases as the infectivity of the source case increases; while administrative control measures are the most effective because they substantially reduce the rate of infection .…”

Section: Introductionmentioning

confidence: 98%

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Mathematical Model to Simulate Tuberculosis Disease Population Dynamics

Koriko¹,

Yusuf²

2008

American J. of Applied Sciences

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A mathematical model to depict Tuberculosis disease population dynamics was presented. The model population was compartmentalised as appropriate and the resulting model equations were solved numerically while different instances of the disease transmission were simulated. The graphical profiles of the various sub-populations with time were presented and discussed based on the results from our simulations. Also, the disease-free and endemic equilibrium of the system were established and analyzed for stability.

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Section: Resultssupporting

confidence: 87%

Section: Introductionmentioning

confidence: 98%

Mathematical Model to Simulate Tuberculosis Disease Population Dynamics

Koriko¹,

Yusuf²

2008

American J. of Applied Sciences

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“…Gammaitoni and Nucci's model (where the initial quanta level = 0) is based on the rate of change in quanta levels through time [10,15]:…”

Section: Resultsmentioning

confidence: 99%

The risk of airborne influenza transmission in passenger cars

2011

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SUMMARYTravel in passenger cars is a ubiquitous aspect of the daily activities of many people. During the 2009 influenza A(H1N1) pandemic a case of probable transmission during car travel was reported in Australia, to which spread via the airborne route may have contributed. However, there are no data to indicate the likely risks of such events, and how they may vary and be mitigated. To address this knowledge gap, we estimated the risk of airborne influenza transmission in two cars (1989 model and 2005 model) by employing ventilation measurements and a variation of the Wells–Riley model. Results suggested that infection risk can be reduced by not recirculating air; however, estimated risk ranged from 59% to 99·9% for a 90-min trip when air was recirculated in the newer vehicle. These results have implications for interrupting in-car transmission of other illnesses spread by the airborne route.

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“…Again, this is neither insignificant, nor complete protection. Furthermore, modelling studies 474,475 suggest that combining simple disposable respirators with enhanced air disinfection can lower the risk substantially. For very high-risk procedures, for example, for chest surgery, bronchoscopy, or autopsy of patients with known or suspected MDR tuberculosis, powered air purifying respirators (PAPRs) can be used, which increase the protection factor to more than 90% because the breathing space is under positive pressure.…”

Section: Respiratory Protectionmentioning

confidence: 99%