03224nas a2200637   4500000000100000008004100001260003400042653001300076653002500089653001600114653002000130653003000150100001700180700001200197700001600209700001600225700001500241700001300256700001500269700001300284700001300297700001300310700001200323700001300335700001300348700001300361700001300374700001300387700001300400700001200413700001200425700001200437700001200449700001300461700001500474700001300489700001300502700001100515700001400526700001400540700001600554700001400570700001500584700001800599700001400617700001300631700002100644700001500665700001500680245012900695856008700824300001400911490000700925520162900932022002502561       2024                            d  bOxford University Press (OUP)10aTrachoma10aOperational planning10aElimination10aensemble models10aDistric-level forecasting1 aSrivathsan A1 aAbdou A1 aAl-Khatib T1 aApadinuwe S1 aBadiane MD1 aBucumi V1 aChisenga T1 aKabona G1 aKabore M1 aKanyi SK1 aBella L1 aM’po N1 aMasika M1 aMinnih A1 aSitoe HM1 aMishra S1 aOlobio N1 aOmar FJ1 aPhiri I1 aSanha S1 aSeife F1 aSharma S1 aTekeraoi R1 aTraore L1 aWatitu T1 aBol YY1 aBorlase A1 aDeiner MS1 aRenneker KK1 aHooper PJ1 aEmerson PM1 aVasconcelos A1 aArnold BF1 aPorco TC1 aHollingsworth TD1 aLietman TM1 aBlumberg S00aDistrict-Level Forecast of Achieving Trachoma Elimination as a Public Health Problem By 2030: An Ensemble Modelling Approach  uhttps://academic.oup.com/cid/article-pdf/78/Supplement_2/S101/57334404/ciae031.pdf  aS101-S1070 v783 a<p>Assessing the feasibility of 2030 as a target date for global elimination of trachoma, and identification of districts that may require enhanced treatment to meet World Health Organization (WHO) elimination criteria by this date are key challenges in operational planning for trachoma programmes. Here we address these challenges by prospectively evaluating forecasting models of trachomatous inflammation–follicular (TF) prevalence, leveraging ensemble-based approaches. Seven candidate probabilistic models were developed to forecast district-wise TF prevalence in 11 760 districts, trained using district-level data on the population prevalence of TF in children aged 1–9 years from 2004 to 2022. Geographical location, history of mass drug administration treatment, and previously measured prevalence data were included in these models as key predictors. The best-performing models were included in an ensemble, using weights derived from their relative likelihood scores. To incorporate the inherent stochasticity of disease transmission and challenges of population-level surveillance, we forecasted probability distributions for the TF prevalence in each geographic district, rather than predicting a single value. Based on our probabilistic forecasts, 1.46% (95% confidence interval [CI]: 1.43–1.48%) of all districts in trachoma-endemic countries, equivalent to 172 districts, will exceed the 5% TF control threshold in 2030 with the current interventions. Global elimination of trachoma as a public health problem by 2030 may require enhanced intervention and/or surveillance of high-risk districts.</p>
  a1058-4838, 1537-6591