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Use of a mathematical model to estimate tuberculosis transmission risk in an Internet cafe.

ABSTRACT: OBJECTIVE: People who live under fragile living conditions may stay overnight in Internet cafés in urban areas. An outbreak of tuberculosis (TB), the routes of which were possibly related to such a facility, has been reported. The purpose of this study was to use a mathematical model to quantify the public health risk of TB infection in such a facility. METHODS: The reproduction number for airborne infection in an enclosed space (R (A)) was estimated using a Wells-Riley model. First, we estimated R (A) for the TB infection based on the report of the TB outbreak in the Internet café. Second, TB infectious dose, number of days of exposure, and air-exchange rate in the facility were varied to estimate the effect of TB risk settings and environmental factors. RESULTS: We assumed that TB patients and 59 susceptible subjects stayed for 150 days in a room where the air-exchange rate was five per hour. Using the estimated median R (A) of 44.14, the TB infection rate was 74.6%. This result was similar to the epidemiological report that the TB infection rate among employees in the Internet café was 70%. The median R (A) increased linearly as the number of days of exposure increased. The slope of the change in median R (A) divided by the change in the number of days of exposure increased exponentially as air-exchange rate decreased; thus air ventilation in a facility may be essential to prevent TB infection. CONCLUSIONS: Appropriate air ventilation in facilities such as Internet cafés is needed as part of a TB-control program in metropolitan areas.

SUBMITTER: Furuya H

PROVIDER: S-EPMC2684774 | biostudies-other | 2009 Mar

REPOSITORIES: biostudies-other

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Project description:BackgroundAlthough an increase in hepatitis C virus (HCV) prevalence from Northern to Southern Italy has been reported, the burden of asymptomatic individuals in different Italian regions is currently unknown.MethodsA probabilistic approach, including a Markov chain for liver disease progression, was applied to estimate current HCV viraemic burden. The model defined prevalence by geographic area using an estimated annual historical HCV incidence by age, treatment rate, and migration rate from the Italian National database. Viraemic infection by age group was estimated for each region by main HCV transmission routes of individuals for stage F0-F3 (i.e. patients without liver cirrhosis and thus potentially asymptomatic) and F4 (patients with liver cirrhosis, thus potentially symptomatic).ResultsBy January 2020, it was estimated that there were 409,184 Italian individuals with HCV (prevalence of 0.68%; 95% CI: 0.54-0.82%), of which 300,171 (0.50%; 95% CI: 0.4-0.6%) were stage F0-F3. Considering all individuals with HCV in stage F0-F3, the geographical distributions (expressed as the proportion of HCV infected individuals by macroarea within the overall estimated number of F0-F3 individuals and prevalence values, expressed as the percentage of individuals with HCV versus the overall number of individuals for each macroarea) were as follows: North 42.1% (0.45%; 95% CI: 0.36-0.55%), Central 24.1% (0.61%; 95% CI: 0.48-0.74%), South 23.2% (0.50%; 95% CI: 0.4-0.61%), and the Isles 10.6% (0.49%; 95% CI: 0.39-0.59%). The population of people who inject drugs accounted for 50.4% of all individuals infected (F0-F3). Undiagnosed individuals (F0-F3) were ~ 15 years younger (⁓ 50 years) compared with patients with stage F4 (⁓ 65 years), with similar age distributions across macroareas. In contrast to what has been reported on HCV epidemiology in Italy, an increasing trend in the proportion of potentially undiagnosed individuals with HCV (absolute number within the F0-F3) from South (23.2%) to North (42.1%) emerged, independent of similar regional prevalence values.ConclusionThis targeted approach, which addresses the specific profile of undiagnosed individuals, is helpful in planning effective elimination strategies by region in Italy and could be a useful methodology for other countries in implementing their elimination plans.

Project description:IntroductionThe ongoing civil war in Yemen has severely restricted imports of food and fuel, disrupted livelihoods and displaced millions, worsening already high pre-war levels of food insecurity. Paired with frequent outbreaks of disease and a collapsed health system, this has brought rates of wasting in children under five to the country's highest recorded levels, which continue to increase as the crisis worsens and aid becomes increasingly limited. In their planning of services to treat and prevent wasting in children, humanitarian agencies rely on a standard calculation to estimate the expected number of cases for the coming year, where incidence is estimated from prevalence and the average duration of an episode of wasting. The average duration of an episode of moderate and severe wasting is currently estimated at 7.5 months-a globally-used value derived from historical cohort studies. Given that incidence varies considerably by context-where food production and availability, treatment coverage and disease rates all vary-a single estimate cannot be applied to all contexts, and especially not a highly unstable crisis setting such as Yemen. While recent studies have aimed to derive context-specific incidence estimates in several countries, little has been done to estimate the incidence of both moderate and severe wasting in Yemen.MethodsIn order to provide context-specific estimates of the average duration of an episode, and resultingly, incidence correction factors for moderate and severe wasting, we have developed a Markov model. Model inputs were estimated using a combination of treatment admission and outcome records compiled by the Yemen Nutrition Cluster, 2018 and 2019 SMART surveys, and other estimates from the literature. The model derived estimates for the governorate of Lahj, Yemen; it was initialized using August 2018 SMART survey prevalence data and run until October 2019-the date of the subsequent SMART survey. Using a process of repeated model calibration, the incidence correction factors for severe wasting and moderate wasting were found, validating the resulting prevalence against the recorded value from the 2019 SMART survey.ResultsThe average durations of an episode of moderate and severe wasting were estimated at 4.86 months, for an incidence correction factor k of 2.59, and 3.86 months, for an incidence correction factor k of 3.11, respectively. It was found that the annual caseload of moderate wasting was 36% higher and the annual caseload of severe wasting 58% higher than the originally-assumed values, estimated with k = 1.6.ConclusionThe model-derived incidence rates, consistent with findings from other contexts that a global incidence correction factor cannot be sufficient, allow for improved, context-specific estimates of the burden of wasting in Yemen. In crisis settings such as Yemen where funding and resources are extremely limited, the model's outputs holistically capture the burden of wasting in a way that may guide effective decision-making and may help ensure that limited resources are allocated most effectively.

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Use of a mathematical model to estimate tuberculosis transmission risk in an Internet cafe.

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