Importance of Coverage and Endemicity on the Return of Infectious Trachoma after a Single Mass Antibiotic Distribution

Trachoma, caused by ocular chlamydia infection, is the most common infectious cause of blindness in the world. The World Health Organization (WHO) recommends the SAFE strategy (eyelid surgery, antibiotics, facial hygiene, environmental improvements) for trachoma control. Oral antibiotics reduce the transmission of ocular chlamydia, but re-infection of treated individuals is common. Therefore, the WHO recommends annual mass antibiotic treatments to the entire village. The success of treatment is likely based on many factors, including the antibiotic coverage, or percentage of villagers who receive antibiotics. However, no studies have analyzed the importance of antibiotic coverage for the reduction of ocular chlamydia. Here, we performed multivariate regression analyses on data from a clinical trial of mass oral antibiotics for trachoma in a severely affected area of Ethiopia. At the relatively high levels of antibiotic coverage in our study, coverage was associated with post-treatment infection at two months, but not at six months. The amount of infection at baseline was strongly correlated with post-treatment infection at both two and six months. These results suggest that in areas with severe trachoma treated with relatively high antibiotic coverage, increasing coverage even further may have only a short-term benefit

A rationale for continuing mass antibiotic distributions for trachoma

BACKGROUND: The World Health Organization recommends periodic mass antibiotic distributions to reduce the ocular strains of chlamydia that cause trachoma, the world's leading cause of infectious blindness. Their stated goal is to control infection, not to completely eliminate it. A single mass distribution can dramatically reduce the prevalence of infection. However, if infection is not eliminated in every individual in the community, it may gradually return back into the community, so often repeated treatments are necessary. Since public health groups are reluctant to distribute antibiotics indefinitely, we are still in need of a proven long-term rationale. Here we use mathematical models to demonstrate that repeated antibiotic distributions can eliminate infection in a reasonable time period. METHODS: We fit parameters of a stochastic epidemiological transmission model to data collected before and 6 months after a mass antibiotic distribution in a region of Ethiopia that is one of the most severely affected areas in the world. We validate the model by comparing our predicted results to Ethiopian data which was collected biannually for two years past the initial mass antibiotic distribution. We use the model to simulate the effect of different treatment programs in terms of local elimination of infection. RESULTS: Simulations show that the average prevalence of infection across all villages progressively decreases after each treatment, as long as the frequency and coverage of antibiotics are high enough. Infection can be eliminated in more villages with each round of treatment. However, in the communities where infection is not eliminated, it returns to the same average level, forming the same stationary distribution. This phenomenon is also seen in subsequent epidemiological data from Ethiopia. Simulations suggest that a biannual treatment plan implemented for 5 years will lead to elimination in 95% of all villages. CONCLUSION: Local elimination from a community is theoretically possible, even in the most severely infected communities. However, elimination from larger areas may require repeated biannual treatments and prevention of re-introduction from outside to treated areas

Reduction and Return of Infectious Trachoma in Severely Affected Communities in Ethiopia

Trachoma is one of the leading causes of blindness in the developing world. The World Health Organization has a multi-pronged approach to controlling the ocular chlamydial infection that causes the disease, including distributing antibiotics to entire communities. Even a single community treatment dramatically reduces the prevalence of the infection. Unfortunately, infection returns back into communities after treatment, at least in severely affected areas such as rural Ethiopia. Here, we assess whether additional scheduled treatments in 16 communities in the Gurage area of Ethiopia further reduce infection, and whether the disease returns after distributions are stopped. In communities with the highest levels of trachoma ever studied, we find that repeated mass oral azithromycin distributions gradually reduce the prevalence of trachoma infection in a community, as long as these treatments are given frequently enough and to enough people in the community. Unfortunately, infection returns into the communities after the last treatment. Sustainable changes or complete local elimination of infection will be necessary to stop the return of ocular chlamydial in communities with very high prevalence of the disease

Risk Factors for Ocular Chlamydia after Three Mass Azithromycin Distributions

Trachoma, which is the leading infectious cause of blindness worldwide, is caused by repeated ocular infection with Chlamydia trachomatis. Treatment for trachoma includes mass azithromycin treatments to the entire community. The World Health Organization recommends at least 3 rounds of annual mass antibiotic distributions in areas with trachoma, with further mass treatments based on the prevalence of trachoma. However, there are other options for communities that have received several rounds of treatment. For example, programs could continue antibiotic treatments only in those households most likely to have infected individuals. In this study, we performed trachoma monitoring on children from 12 Ethiopian communities one year after a third mass azithromycin treatment, and conducted a household survey at the same time. We found that children were more likely to be infected with ocular chlamydia if they had ocular inflammatory signs or ocular discharge, or if they had missed the preceding antibiotic treatment, had an infected sibling, or came from a larger community. These risk factors suggest that after mass azithromycin treatments, trachoma programs could consider continuing antibiotic distributions to households that have missed prior antibiotic distributions, in households with children who have the clinical signs of trachoma, and in larger communities

Clinical Activity and Polymerase Chain Reaction Evidence of Chlamydial Infection after Repeated Mass Antibiotic Treatments for Trachoma

It is unclear how the prevalence of clinically active trachoma correlates with the prevalence of ocular chlamydial infection at the community level. In 24 villages from a cluster-randomized clinical trial of mass azithromycin distributions in Ethiopia, the correlation between the prevalence of clinical activity (on examination) and chlamydial infection (by polymerase chain reaction) was moderately strong before mass antibiotic treatments (Pearson's correlation coefficient r = 0.75, 95% confidence interval [CI] = 0.52–0.87), but decreased at each time point during four biannual treatments (at 24 months, r = 0.15, 95% CI = −0.14–0.41). One year after the final treatment, the correlation coefficient had increased, but not to the pre-treatment level (r = 0.55, 95% CI = 0.30–0.73). In a region with hyperendemic trachoma, conjunctival examination was a useful indicator of the prevalence of chlamydial infection before treatments, less useful during mass treatments, but regained utility by one year after treatments had stopped

Predicted chlamydial infection after a single mass azithromycin treatment, with varying levels of antibiotic coverage.

<p>Post-treatment chlamydial prevalence in 1–5 year old children was calculated for a hypothetical community treated with a single mass azithromycin treatment, in which 48.9% of 1–5 year old children were infected at baseline. Antibiotic coverage was significantly associated with post-treatment infection at two months (2A; <i>R</i>² = 0.53, <i>p</i> = 0.007), but not at six months (2B; <i>R</i>² = 0.35, <i>p</i> = 0.31). The upper and lower curves are the boundaries of the 95% confidence interval for the predicted mean.</p

Kernel density estimate showing the distribution of antibiotic coverage.

<p>Antibiotic coverage data was available for 38 of 40 villages. The density plot was computed using the Epanechnikov kernel function, Sheather-Jones plug-in bandwidth estimate, and upper boundary correction using the renormalization method.</p