In this study, we analyzed the cross-sectional distribution of TB cases within households in urban Lima, Peru, to estimate the relative contributions of household and community transmission, the average time between household cases, and the protective immunity conferred by a previous exposure. Our findings rely on data that are often routinely collected within well-functioning TB programs, and our parameter estimates are consistent with previous estimates derived from more labor-intensive approaches such as cohort studies and molecular epidemiology studies. The results of this study will contribute to the practical design of case-finding strategies and help elucidate TB transmission dynamics and parameterize more accurate epidemic models.
Consistent with findings from other high burden settings, we find that for the time covered by this analysis a high proportion of nonindex case patients in households with a previously identified case were probably infected in the community rather than through household transmission. Our finding that >65% of the nonindex cases were due to community transmission is comparable with the results of a recent molecular epidemiologic study in Cape Town, South Africa, which compared DNA fingerprints of M. tuberculosis
isolates from households with ≥2 cases of TB. This study found that 61% of paired isolates had mismatching fingerprints, indicating that at least
61% of secondary cases were due to community transmission [15
]. This result would underestimate the true proportion of cases due to community transmission if some community transmission events involved the same strain that infected a household index case.
One of the challenges in TB epidemiology is the long time scales of transmission, infection, and disease during which other factors such as disease prevalence or household composition may have changed. The methods presented here, like other techniques for quantifying TB epidemiology (such as [15
]), therefore result in parameter estimates that represent averages over the time period of the analysis. In Peru, the estimated incidence of all forms of TB has fallen by ~60% since 1990 [2
]; this decreasing incidence is expected to result in decreases in the risk of community-acquired disease. By restricting the time period of the analysis, we observed a decrease in both the risk of community- and household-acquired disease, as well as a small decrease in the percentage of cases resulting from community transmission, from 70% to 65%. We note that the percentage of community-acquired cases may also have been overestimated if household members with active TB died before the study.
The elevated risk of TB disease in household contacts of index cases did not scale proportionately with the number of cases in the household. This is consistent with the idea that previous TB exposure provides some protection against future disease with rechallenge [30
]. By using residence with a single case as a unit of exposure, we were able to estimate the degree of protection afforded by a previous exposure. In future studies, additionally collecting the infection status of household members would allow more detailed conclusions about the role of latent infection in the development of disease. Our estimate of 35% protection is lower than that of Sutherland and colleagues, who used trends in population level estimates of infection and disease in the Netherlands to estimate that previous exposure afforded 65% protection [30
], but our results are consistent with data from England and Wales in the early part of the 20th century [32
]. Similarly, the incidence rate of disease in individuals who had positive skin test results at baseline in the control arm of a BCG vaccine trial suggested a 50% protective effect associated with infection [33
]. The reduced protection found in our study might reflect a biologic difference due to multiple reinfections in this high-burden area, or the difference between protective immunity conferred by exposure to drug-sensitive and drug-resistant disease. Observed a saturation effect in the number of cases per household, suggesting that even with high levels of exposure some individuals do not develop disease.
We propose that these types of household data may be used to inform the minimum duration that household contacts should be monitored and actively assessed for disease after the discovery of an infectious household case. We estimated a median time between diagnoses within households of 3.5 years, although the wide variance in time between successive cases indicates that secondary cases may occur many years after the primary case. This estimate lies on the upper end of population-wide estimates of 1–7 years calculated by Blower et al [35
]. The extended tail of our distribution is quantitatively similar to previous estimates from population-level data in Europe [35
] and South Africa [38
] and reflects a small number of secondary cases occurring decades after an index case. In these situations, molecular fingerprinting can distinguish between reinfection and reactivation.
The model used in this study necessitated a number of simplifying assumptions. First, we modeled the transmission process as if it began with the first case of active disease in the household. In reality, household contacts may have had a prior infection from community exposure that provided some immunity to infection from their household contact. This assumption may alter our estimate of within household transmission by overestimating the impact of the first case, although the effect of this assumption is reduced if there is widespread and uniform exposure in the community. The effect of immunity was estimated from a ratio of 2 models with the same assumption, and therefore it should also be robust.
In this analysis, we used the cumulative number of cases among adults within a household to infer transmission parameters. We excluded persons <15 years of age because of the different natural history of disease in children. A potential extension of the model could include children to understand the relative risks faced by children in households with TB cases and their role in transmission [39
]. Additionally, stratifying adults by age could provide more detailed estimates of community transmission over time.
We parameterized our model with data from a cohort study of households living with multidrug-resistant patients. This means that our estimate of community-acquired disease will not reflect community prevalence and will be greater than population-wide estimates. Repeating this type of analysis among household contacts of patients with drug-sensitive TB would lead to improved estimates of prevalence and an increased understanding of the mechanisms involved in the development and transmission of drug-resistant strains.