^{1}

^{1}

^{2}

^{3}

^{*}

^{1}

^{4}

^{5}

^{6}

^{7}

^{1}

^{2}

^{3}

^{6}

The authors have declared that no competing interests exist.

Conceived and designed the experiments: TML TCP FL SKW. Performed the experiments: FL TCP TML SKW HM BM. Analyzed the data: FL TCP TML BM KJR RLB TCQ. Contributed reagents/materials/analysis tools: SKW TML TCP FL. Wrote the paper: TCP FL TML KJR SKW RLB. Contributed to the collection of clinical data: SKW BM HM. Contributed to the cleaning and management of data: BM.

Trachoma programs have dramatically reduced the prevalence of the ocular chlamydia that cause the disease. Some have hypothesized that immunity to the infection may be reduced because of program success in reducing the incidence of infection, and transmission may then increase. Longitudinal studies of multiple communities would be necessary to test this hypothesis. Here, we quantify transmission using an estimated basic reproduction number based on 32 communities during the first, second, and third years of an antibiotic treatment program. We found that there is little to no increase in the basic reproduction number over time. The estimated linear trend in the basic reproduction number,

Trachoma, caused by repeated infections by the ocular strains of

The World Health Organization has targeted trachoma for elimination by the year 2020

Communities were monitored as part of a cluster-randomized, trachoma treatment trial in Tanzania

The study received ethical approval from institutional review board (IRB) of the Johns Hopkins University School of Medicine, the University of California San Francisco, and the Tanzanian National Institute for Medical Research, and was carried out in accordance with the Declaration of Helsinki. All subjects provided informed consent. The informed consent given was oral, because 1) verbal consent is the most ethical way to obtain consent, due to the high illiteracy rates in the study area, 2) IRB approved the use of the oral consent procedure for this study, 3) this oral consent is documented on the registration form for each study participant prior to examination in the field.

We constructed a stochastic transmission model of transmission of _{j}^{−1}). Between periods of treatment, we assumed that the probability _{i}

To estimate the transmission coefficient, we used data collected six months and twelve months after each treatment. The model was fit to each of three years. For comparing transmission rates, we initialized the model with observations taken six months after treatment, and we estimated the transmission parameter based on values observed six months after that. Thus, we modeled the time periods from 6 to 12 months, 18 to 24 months, and 30 to 36 months.

For each year, initial values for _{i}_{j}_{j}_{j}_{j}_{j}

We assumed specific values of ^{−1}), in the transmission coefficient per year by finding maximum likelihood estimates of _{1} and _{2} = _{1}+_{3} = _{1}+2

Scenario | Mean duration of infection (1/ |
Estimated |
||||

Overall | 1^{st} year |
2^{nd} year |
3^{rd} year |
|||

Base Case | 6-month | 1.39 (1.28, 1.49) | 1.40 (1.26, 1.55) | 1.38 (1.09, 1.67) | 1.35 (0.92, 1.78) | −0.025 (−0.167, 0.117) |

Sensitivity Analyses | 18-month | 1.90 (1.62, 2.19) | 11.87 (1.48, 2.26) | 1.92 (1.15, 2.70) | 1.96 (0.82, 3.13) | 0.054 (−0.326, 0.434) |

12-month | 1.64 (1.45, 1.84) | 1.64 (1.37, 1.91) | 1.65 (1.12, 2.18) | 1.66 (0.87, 2.45) | 0.012 (−0.248, 0.273) | |

3-month | 1.26 (1.19, 1.31) | 1.28 (1.20, 1.37) | 1.24 (1.08, 1.41) | 1.20 (0.96, 1.45) | −0.041 (−0.122, 0.039) |

: the 95% CI of

We also estimated an alternative model in which instead of varying the transmission coefficient over time, we instead assumed a constant transmission coefficient, and instead modeled the recovery rate in year ^{−1} year^{−1}) is the annual change in recovery rate.

Previous models have estimated the duration of infection 1/

All calculations were performed using

The numbers of 0–5 year-old children tested for the presence of ocular chlamydia were 3199 (baseline), 3198 (month 6), 3191 (month 12), 3200 (month 18), 3199 (month 24), 3194 (month 30), and 3153 (month 36). The estimated prevalence of ocular chlamydial infection by PCR at baseline was 22.0% (standard deviation 10.1%), at 6 months 10.5% (SD 4.7%), at 12 months 13.0% (SD 6.4%), at 18 months 7.1% (SD 4.4%), at 24 months 8.6% (SD 7.3%), at 30 months 3.5% (SD 2.5%), and at 36 months 4.7% (SD 3.3%).

Assuming a mean duration of infection of six months with beta-binomial prior (choosing the shape parameters to match the observed mean and variance of all villages cross sectionally at each initialization time), we found the basic reproduction number to be

The estimated change per year in the reproductive number, ^{−1}; twelve months, ^{−1}; eighteen months, ^{−1}. Regardless of the assumed duration of infection, we find point estimates for the annual change in the basic reproduction number which are near zero. The confidence intervals are wider when a longer duration of infection is assumed, and these intervals include zero (i.e., no change) in every scenario.

Similar findings were obtained when a different choice of prior was used. Specifically, we assumed a uniform distribution as the prior distribution for the number of infected individuals; this yielded an overall ^{−1}. Choosing other values of the mean duration together with the uniform prior similarly yielded the following results: three months, ^{−1}; twelve months, ^{−1}; eighteen months, ^{−1}.

We estimated the change in the recovery rate ^{−1} year^{−1}, with the estimated recovery rate in the first year given by 0.177 (95% CI: 0.154 to 0.20) month^{−1} year^{−1}. This model yields a substantially similar interpretation as the previous model.

Using a transmission model and data collected from a 32-community, cluster-randomized clinical trial in Tanzania, we found no evidence of increased transmission from the 1^{st} through the 3^{rd} year of treatment. In fact, our estimates of the reproduction number of the infection were very similar for each year, suggesting no loss of immunity.

Others have proposed an arrested immunity hypothesis, in which the development of protective immune responses is decreased as the duration of chlamydial infection is decreased. It has been suggested that an increased incidence of infection in the presence of a decreased seroprevalence in Finland and British Columbia is due to this phenomenon

There are several reasons this analysis of these data might fail to detect an increase in transmission, even if such an increase in fact exists. Two years may not be long enough for immunity to wane, although the period in which an earlier study suggested waning was only one year

Models have predicted that if transmission per infectious case remains constant, repeated distributions can eliminate infection from even the most severely affected communities

We thank the data and safety monitoring committee including Douglas Jabs, MD, MBA (chair), Antoinette Darville, MD, Maureen Maguire, PhD, and Grace Saguti, MD, who were generous with their time and advice, and met before and during the study.