INTRODUCTION
Trachoma causes blindness among the poorest people on the planet.1 Trachomatous blindness arises from repeated conjunctival Chlamydia trachomatis infection and the eyelid scarring that accumulates from the associated episodes of active (inflammatory) trachoma.2 The disease can be eliminated as a public health problem through a four-pronged strategy summarized by the acronym SAFE: surgery (S) for individuals with advanced, blinding disease; antibiotics (A) to clear C. trachomatis infection; and facial cleanliness (F) and environmental improvement (E) to reduce ocular C. trachomatis transmission.
The A, F, and E components of SAFE are delivered at the evaluation unit (EU) level. Evaluation units are generally populations of 100,000–250,000 people3; however, for practical reasons (including expediency at program inception3 or the size of local administrative divisions for healthcare management purposes4), they are sometimes smaller4 or larger4,5 than this. Five annual rounds of EU-wide mass drug administration (MDA) of antibiotics active against ocular C. trachomatis6 are undertaken wherever the prevalence of the active trachoma sign trachomatous inflammation—follicular (TF7) in 1- to 9-year-olds is ≥ 30%. Three annual rounds are undertaken wherever the TF prevalence is 10–29.9%. Where the TF prevalence is 5.0–9.9%, the WHO recommends targeted treatment3; in recent years, this has been programmatically applied by targeting all EU residents in a single round of MDA8; the alternative targeting approaches of offering antibiotics only to individuals,9 households,10–12 or communities13 with active trachoma having been assessed as likely ineffective, impractical at scale, or both. Antibiotic MDA for trachoma should always be accompanied by implementation of F and E; however, the evidence base for F and E is weaker than that for A.14,15
Because decisions concerning implementation of SAFE’s A component rest on EU-level prevalence of TF, reliable TF prevalence data are critical. Recently, the global trachoma program has made important investments in appropriately scoping out16 and mapping17–21 suspected endemic populations using standardized, quality-controlled, and quality-assured approaches.22–24 Where baseline TF prevalence is < 5%, the A component is not indicated for trachoma elimination purposes, but the need for interventions to improve access to water and sanitation may be highlighted if current access is suboptimal.25 Where baseline TF prevalence is ≥ 5%, A, F, and E are indicated as noted earlier, with impact surveys due 6–12 months after the last planned round of MDA.26 Programs use impact survey TF prevalence to determine whether further MDA rounds should be planned. Impact survey TF prevalence < 5% signals an end to MDA for trachoma elimination purposes and the start of a 2-year surveillance period. At the end of those 2 years, a pre-validation surveillance survey is undertaken to ensure that TF prevalence has not recrudesced to ≥ 5%.26
Baseline,21 impact,27 and pre-validation surveillance28 surveys are generally all performed using population-based, two-stage cluster sampling.29 Survey costs are not insignificant.30–32 Trachoma programs are currently undergoing considerable expansion in an effort to achieve the World Health Assembly–endorsed goal of global elimination of trachoma as a public health problem.33,34 During a session of the 2018 meeting of the Coalition for Operational Research on neglected tropical diseases (NTDs), discussion focused on the proportion of EUs undergoing trachoma impact surveys in a defined period returning a TF prevalence estimate above the elimination threshold, a proportion sometimes referred to as the failure rate. This rate was said to be higher than the analogous failure rate of lymphatic filariasis transmission assessment surveys, with the implication being that money for trachoma elimination was being inefficiently spent on surveys conducted too soon. It led us to wonder: Is a nonzero failure rate necessarily bad? Here, we demonstrate that the answer is no, by modeling the financial cost of undertaking MDA with and without conducting impact surveys. And, because in this context failure turns out to be helpful, we will henceforth use the more neutral term continuation rate to refer to the proportion of EUs undergoing impact surveys that derive a renewed mandate for MDA.
MATERIALS AND METHODS
To obtain an impact survey continuation rate of 0% (and thereby save money on monitoring and evaluation by not needing to repeat impact surveys after further rounds of MDA), all impact surveys would need be delayed until a TF prevalence < 5% was thought to be virtually guaranteed. We therefore compared the cost of using impact surveys to guide decision-making on ongoing annual MDA with the cost of simply continuing MDA for another year, considering only the financial costs to the trachoma program in a single year of its operation.
We hypothesized a set of trachoma-endemic EUs in which, at the beginning of the program year, the recommended number of annual rounds of MDA for trachoma elimination purposes had already been completed. Assuming appropriate antibiotics were available, the trachoma program manager could—in theory—choose between two strategies:
- (a)undertake an impact survey in each EU, then decide whether to stop or continue MDA in the EU on the basis of the survey outcome; or
- (b)undertake another round of MDA in each EU, postponing impact surveys until the next year or beyond.
We know that
Our choices of, for example, per-capita GDP and population density when deriving
We obtained empirical data on
As a case example, we compared the cost of implementing each strategy within the trachoma elimination program of the United Republic of Tanzania for 2017 and 2018. For this analysis, we used survey and cost data collected retrospectively from the actual surveys implemented during that period.
RESULTS
From January 1, 2017 to December 31, 2018, Tropical Data supported trachoma programs to complete 538 impact surveys in 25 countries, representing 92% of all impact surveys completed for trachoma globally during that 2-year period.
A total of 170 (32%) of those 538 impact surveys returned estimates of TF prevalence in 1- to 9-year-olds of ≥ 5%, indicating MDA continuation. Continuation rates ranged by country from 0% to 100% of EUs. Fourteen of 25 countries had nonzero continuation rates.
For EUs containing a mean of 100,000 people, the median cost of continuing MDA without doing impact surveys would be USD 28,957 per EU per year, whereas the median cost of doing impact surveys and continuing MDA only where indicated by TF prevalence would be USD 17,564 (Table 1). Continuing MDA without impact surveys becomes advantageous (in financial cost terms) only when the continuation rate exceeds 71%.
Cost per trachoma-endemic EU in a single programmatic year for (a) undertaking an impact survey in each EU, and then making a decision on whether to stop or continue annual antibiotic MDA for trachoma elimination purposes in that EU on the basis of the outcome; and (b) simply continuing MDA without first conducting impact surveys, and the continuation rate at which financial costs for the two strategies equalize, for different mean EU populations
| Cost per EU of impact surveys then MDA where indicated*, 2017 USD† | Cost per EU of continuing MDA without first conducting impact surveys‡, 2017 USD†, | Impact survey continuation rate at which financial costs equalize, %† | |
|---|---|---|---|
| 50,000 | 14,751 (10,503–18,219) | 20,166 (12,410–25,337) | 58 (47–60) |
| 100,000 | 17,564 (12,158–21,694) | 28,957 (17,581–36,197) | 71 (62–72) |
| 150,000 | 19,715 (13,482–24,507) | 35,679 (21,718–44,987) | 76 (69–77) |
| 200,000 | 21,536 (14,474–27,320) | 41,368 (24,820–53,778) | 79 (73–81) |
| 250,000 | 23,190 (15,633–29,140) | 46,539 (28,440–59,466) | 82 (77–82) |
| 500,000 | 29,809 (19,770–38,241) | 67,223 (41,368–87,907) | 87 (84–88) |
EU = evaluation unit; IQR = interquartile range; MDA = mass drug administration. Calculations were based on the global median (and IQR of) impact survey costs from Stelmach et al.,32 the 2017–2018 global Tropical Data impact survey continuation rate of 32%, and the global median (and 95% CIs of) per-person financial cost of MDA from Fitzpatrick et al.,35 inflated from 2015 USD to 2017 USD using a factor of ×1.0342.
Referred to in the text as “strategy (a).”
First figure in each cell uses the median survey and MDA costs; figures in parentheses reflect the IQR of survey costs and 95% CI of MDA costs.
Referred to in the text as “strategy (b).”
In the United Republic of Tanzania in the 2 years from January 1, 2017 to December 31, 2018, 20 impact surveys were required. The continuation rate was 6/20 (30%). The cost of not doing impact surveys and just undertaking MDA in each of those 20 EUs (strategy [b]) would have been $409,721. The cost of the process actually performed—undertaking impact surveys and implementing MDA only where indicated (strategy [a])—was $307,790, a saving of $101,931 (25%, Table 2). Based on the local cost of MDA in 2017–2018 ($0.0981 per person, Table 2), this is equivalent to the cost of undertaking MDA for more than one million people.
Retrospective estimate of costs to the United Republic of Tanzania’s trachoma elimination program of either (a) undertaking an impact survey in each EU in which one was due in 2017 or 2018 and then deciding whether to stop or continue annual antibiotic MDA for trachoma elimination purposes in that EU on the basis of the outcome; or (b) simply continuing MDA without first conducting impact surveys
| District | EU | Year of impact survey | Cost of impact survey (USD) | Estimated population at the time of impact survey | Cost of one round MDA (USD), if needed | Strategy (a) | Strategy (b) | Annual saving achieved using strategy (a) rather than (b) | |
|---|---|---|---|---|---|---|---|---|---|
| Trachomatous inflammation—follicular prevalence category at impact survey (MDA needed?) | Total cost of impact survey + MDA in year of impact survey | Cost of MDA (no impact survey) | |||||||
| Nkasi | Nkasi | 2018 | 8,719.32 | 318,958 | 28,884.11 | < 5% (no) | 8,719.32 | 28,884.11 | 20,164.79 |
| Kalambo | Kalambo | 2018 | 7,610.23 | 235,589 | 21,351.88 | 5–9.9% (yes) | 28,962.11 | 21,351.88 | −7,610.23 |
| Ngara | Ngara | 2018 | 9,501.14 | 386,638 | 16,728.38 | < 5% (no) | 9,501.14 | 16,728.38 | 7,227.24 |
| Songwe | Songwe | 2018 | 6,546.59 | 153,820 | 10,947.88 | 5–9.9% (yes) | 17,494.47 | 10,947.88 | −6,546.59 |
| Chunya | Chunya | 2018 | 8,673.86 | 163,315 | 12,595.67 | < 5% (no) | 8,673.86 | 12,595.67 | 3,921.80 |
| Bahi | Bahi | 2018 | 6,382.95 | 251,080 | 22,565.15 | < 5% (no) | 6,382.95 | 22,565.15 | 16,182.20 |
| Chemba | Chemba | 2018 | 8,401.14 | 267,014 | 32,301.05 | 5–9.9% (yes) | 40,702.19 | 32,301.05 | −8,401.14 |
| Liwale | Liwale | 2018 | 7,610.23 | 96,427 | 18,195.65 | < 5% (no) | 7,610.23 | 18,195.65 | 10,585.42 |
| Longido | Longido | 2018 | 10,616.59 | 144,410 | 18,468.33 | 5–9.9% (yes) | 29,084.92 | 18,468.33 | −10,616.59 |
| Monduli | Monduli | 2018 | 10,616.59 | 186,477 | 20,565.78 | < 5% (no) | 10,616.59 | 20,565.78 | 9,949.20 |
| Ngorongoro | Ngorongoro | 2018 | 11,611.66 | 204,487 | 24,463.96 | 10–29.9% (yes) | 36,075.61 | 24,463.96 | −11,611.66 |
| Kalambo | Kalambo | 2017 | 10,341.64 | 235,589 | 26,436.67 | 5–9.9% (yes) | 36,778.31 | 26,436.67 | −10,341.64 |
| Kilindi | Kilindi | 2017 | 8,788.41 | 258,372 | 26,248.10 | < 5% (no) | 8,788.41 | 26,248.10 | 17,459.69 |
| Itigi | Itigi | 2017 | 8,427.59 | 127,680 | 14,067.43 | < 5% (no) | 8,427.59 | 14,067.43 | 5,639.83 |
| Manyoni | Manyoni | 2017 | 8,597.45 | 213,010 | 20,933.81 | < 5% (no) | 8,597.45 | 20,933.81 | 12,336.36 |
| Kongwa* | Kongwa south | 2017 | 6,973.86 | 197,409 | 23,779.53 | < 5% (no) | 6,973.86 | 23,779.53 | 7,970.53 |
| Kongwa* | Kongwa north | 2017 | 8,835.14 | 113,042 | < 5% (no) | 8,835.14 | |||
| Chamwino* | Chamwino south | 2017 | 8,256.36 | 155,647 | 39,564.67 | < 5% (no) | 8,256.36 | 39,564.67 | 22,820.48 |
| Chamwino* | Chamwino north | 2017 | 8,487.73 | 147,574 | < 5% (no) | 8,487.73 | |||
| Meatu | Meatu | 2017 | 8,821.82 | 321,781 | 31,622.54 | < 5% (no) | 8,821.82 | 31,622.54 | 22,800.72 |
| Totals | 173,820.28 | 4,179,319 | 409,720.59 | – | 307,709.06 | 409,720.59 | 101,930.53 | ||
EU = evaluation unit; MDA = mass drug administration.
Districts divided into two EUs for impact survey purposes.
DISCUSSION
A trachoma elimination program in which all impact surveys estimate TF to be < 5% has waited too long to do them and will in the meantime have incurred unnecessary intervention costs. Doing surveys to determine whether MDA is still needed is generally cheaper than just continuing MDA. The qualification generally is needed in that statement because the certainty of the conclusion would diminish when survey costs or survey continuation rates rise, when MDA costs fall, or for mean EU populations less than 50,000. This observation underlines the merit of the 2010 WHO recommendation that trachoma program EUs be framed as populations of 100,000–250,000 people,3 a recommendation that tried to balance considerations relating to disease control, ethics, existing administrative divisions, local politics, and program costs. The cost element in that balance was intuitive; the present analyses allow the intuition to be formally tested—and found to be correct. Although it may not be straightforward for health ministries to combine local administrative areas with small populations into a single EU for trachoma elimination purposes, where local administrative areas have very small populations, doing so probably increases the cost efficiency of the elimination program.
Understanding that impact surveys save money even when some EUs fail them is important. The corollary—that a nonzero continuation rate should be welcomed—is even more important because it can seem counterintuitive. Spending money on monitoring and evaluation can make program managers and partners uncomfortable. The proportion of funds that can be spent on monitoring and evaluation is capped in some program grants, and the view is sometimes expressed that funds allocated to these activities would be more productively used for disease control. This ignores the fact that programs must periodically reconfirm the presence of the disease being controlled. We have shown in this article that, assuming EUs are larger than 50,000, and the continuation rate and unit costs are not too dissimilar from those included in our models, surveys save money for the program even in the year that they are performed. The reason for the saving is that MDA is delivered only to people who actually need it.
We note that survey data quality is paramount.23 Misclassifying EUs by conducting surveys with inadequate sample sizes, inappropriate sampling strategies, unstandardized graders, or inappropriate analysis methods invalidates any consideration of the use of surveys to improve cost efficiency. We note also that specific local conditions may fall outside the range of our illustrative calculations. The formulas and code (provided here: https://github.com/mathi-eu/tis-failure) will allow replication or contextual adjustment.
Our analyses are relatively simple. They have several inherent limitations: the first of which is that they include only the financial costs to the program. We ignored the economic costs of the time of survey field-workers, time of survey participants, time of antibiotic distribution staff, and time of antibiotic recipients. Second, the
The potential externalities of completely interrupting transmission of ocular C. trachomatis,43–45 reducing transmission of genital C. trachomatis,46 improving child survival,47,48 or eradicating yaws49–51 might, of course, strengthen the argument for continuing MDA. (Evidence for each of these possible outcomes of MDA is incomplete.) Similarly, if early discontinuation of MDA was strongly associated with later recrudescence of active trachoma, then both the benefit of continuing MDA for longer and the eventual financial cost of not doing so would be likely to increase. We also disregard the externalities involved in undertaking integrated surveys52 and integrated disease control and elimination programs,53 which might significantly affect the economic equation.
An additional limitation of this study comes in considering how to apply its conclusions. Programs that have conducted impact surveys for only a few EUs will have continuation rates that are liable to change profoundly as more local experience accrues. And perhaps more importantly, use of a high continuation rate as the lone metric to justify omitting impact surveys would be to ignore the important nonfinancial considerations outlined earlier.
It is worth noting that the counterfactual scenario that we presented—of simply continuing MDA for trachoma until impact survey failure becomes extremely unlikely—would be difficult to put into practice, for two reasons. First, to make donated drug available, the International Trachoma Initiative (which serves as the steward for Pfizer’s [New York, NY] Zithromax® donation) requires program managers to provide evidence of ongoing need for MDA in the form of high-quality TF prevalence data.8 Without the donation, continuation of MDA would require azithromycin to be purchased, increasing
Although our analysis was driven by trachoma program data, similar considerations apply to other disease elimination efforts in which mass interventions are undertaken. Other NTD programs provide an immediate parallel.58 As a touchstone for the 2030 Agenda for Sustainable Development, the movement to control, eliminate, and eradicate NTDs has few equals, such is the impact of the diseases on the impoverished populations in which they thrive.59 Good data are critical for all.60 We hope that this article will encourage ongoing support for both interventions against these diseases and the high-quality monitoring and evaluation needed to guide implementation.
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