Skip to main content
NCBI home page
Taylor & Francis Open Select logoLink to Taylor & Francis Open Select
. 2018 Dec 31;25(Suppl 1):143–154. doi: 10.1080/09286586.2018.1546877

Prevalence of trachoma in the Republic of Chad: results of 41 population-based surveys

Djoré Dézoumbé a,✉, Djibrine-Atim Djada b, Tyau-Tyau Harba c, Jean-Eudes Biao d, Barka Kali d, Jérôme Bernasconi e, Doniphan Hiron e, Karim Bengraïne e, Susan D’Souza f, Rebecca Willis g, Ana Bakhtiari g, Serge Resnikoff e, Paul Courtright h, Anthony W Solomon, , for the Global Trachoma Mapping Project§i,j,*
PMCID: PMC6444194  PMID: 30806544

ABSTRACT

Purpose: To estimate the prevalence of trachoma in suspected-endemic areas of Chad, and thereby determine whether trachoma is a public health problem requiring intervention.

Methods: We divided the suspected-endemic population living in secure districts into 46 evaluation units (EUs), and used the standardized methodologies of the Global Trachoma Mapping Project. A two-stage cluster-sampling procedure was adopted. In each EU, the goal was to examine at least 1019 children aged 1–9 years by recruiting 649 households; all consenting residents aged ≥ 1 year living in those households were examined. Each participant was examined for trachomatous inflammation—follicular (TF), trachomatous inflammation—intense (TI), and trichiasis.

Results: Two EUs had data that could not be validated, and were excluded from the analysis. GPS data for three other pairs of EUs suggested that EU divisions were inaccurate; data for each pair were combined within the pair. In the 41 resulting EUs, 29,924 households in 967 clusters were visited, and 104,584 people were examined. The age-adjusted EU-level prevalence of TF in 1–9-year-olds ranged from 0.0% to 23.3%, and the age- and gender-adjusted EU-level prevalence of trichiasis in ≥ 15-year-olds ranged from 0.02% to 1.3%. TF was above the WHO elimination threshold in 16 EUs (39%) and trichiasis was above the WHO elimination threshold in 29 EUs (71%). Women had a higher prevalence of trichiasis than did men in 31 EUs (76%). A higher ratio of trichiasis prevalence in women to trichiasis prevalence in men was associated (p = 0.03) with a higher prevalence of trichiasis at EU level.

Conclusion: Public health-level interventions against trachoma are needed in Chad. Over 10,000 people need management of their trichiasis; women account for about two-thirds of this total. The association between a higher ratio of trichiasis prevalence in women to that in men with higher overall trichiasis prevalence needs further investigation.

KEYWORDS: Chad, global trachoma mapping project, prevalence, trachoma, trichiasis, gender

Background

Trachoma, the leading infectious cause of blindness worldwide,1 is a chronic kerato-conjunctivitis caused by the bacterium Chlamydia trachomatis.2 Infections, most commonly occurring in children,3 may lead to sub-epithelial follicles or more pronounced inflammation.4 Repeated infection5,6 can lead to scarring of the conjunctivae7 which, when severe enough, can deform the eyelid and cause eyelashes to touch the globe (trichiasis).4 Uncorrected trichiasis can result in corneal abrasion, ulceration, opacification, and potentially, vision loss and blindness.

In 1993, the World Health Organization (WHO) endorsed the SAFE strategy,8 a comprehensive management plan for elimination of trachoma as a public health problem. SAFE refers to surgery (S) to correct trichiasis, mass distribution of antibiotics (A) to clear infection, and facial cleanliness (F) and environmental improvement (E) to reduce C. trachomatis transmission.9 To determine whether public health-level interventions are required, population-based surveys to generate prevalence estimates of trachomatous inflammation—follicular (TF) and trichiasis are recommended.10,11

Chad is a central African country of approximately 12 million people spread across three distinct ecologic zones: the Sahara Desert, the Sahel, and the Savanna. Currently the country has a total of 33 ophthalmic nurses; 35 ophthalmic technicians; and nine ophthalmologists (approximately one for every 1.5 million people) of whom 5 are in the capital N’Djamena. Though absolute numbers of eye-care personnel are low, Chad is fortunate that 90% of them work in the public sector – specifically in five departments of ophthalmology (within two secondary and three tertiary hospitals) and 21 secondary eye care units.

A number of population-based trachoma prevalence surveys were undertaken in Chad in 1984,12 1985,13 200114 and 200415 (Table 1); however, due to financial constraints, SAFE strategy implementation was not commenced until 2015. The 1984–2004 surveys occurred prior to the recent growth in interest in trachoma elimination,17 and were conducted at region level, covering large populations and wide geographical areas (Table 1). Because of the age and relatively low resolution of existing data, in order to inform programmatic action, baseline mapping or re-mapping was felt to be required.18 We set out to estimate the prevalence of TF in 1–9-year-olds and the prevalence of trichiasis in adults in population units of 100,000–250,000 people in suspected-trachoma-endemic areas of rural Chad.

Table 1.

Findings from trachoma prevalence surveys in Chad, 1984–2004.

Region(s) surveyed Year survey completed Estimated population at time of survey Active trachoma indicator reported Number of 0–9-year-olds examined Active trachoma prevalence in
0–9-year-olds (%) [95% CI]b 		Trichiasis indicator
reported		 Number of adults examined Trichiasis prevalence in (%)b Ref
Lac and Kanem 1984 322,289 F3P3 or F3P2a 213 30.5 Trichiasis in ≥ 15-year-olds 256 5.5 12
Ouaddaï and Biltine 1985 1,558,953 F3P3 or F3P2a 211 27.5 Trichiasis in ≥ 15-year-olds 314 3.5 13
Lac, Kanem, Chari Baguirmi 2001 1,798,240 TF 2046 33.2 [29.2–37.5] Trichiasis in ≥ 15-year-old ♀s 1252 1.3 14
Ouaddaï and Biltine 2001 1,663,512 TF 1906 29.7 [25.6–34.1] Trichiasis in ≥ 15-year-old ♀s 1240 1.7 14
Moyen Chari 2004 757,127 TF 2409 17.5 Trichiasis in ≥ 15-year-old ♀s 1626 1.4 15
Guéra and Salamat 2004 1,072,034 TF 2119 26.9 Trichiasis in ≥ 15-year-old ♀s 1605 6.2 15
Open in a new tab

aIndicators of severe active trachoma in WHO’s 1981 revision of the “FPC” grading system16

bUnadjusted

TF, trachomatous inflammation—follicular; TI, trachomatous inflammation—intense

Materials and methods

Administratively, Chad is divided into 23 regions. Each region (other than the capital, N’Djamena, which has a different internal administrative structure) is divided into two to six health districts, the level at which trachoma elimination activities are implemented.19 There are 61 health districts in total, of which 45 were suspected to have trachoma as a public health problem and therefore to qualify for mapping, based on criteria published elsewhere.20 Surveys were conducted in 2014 and 2015. Due to insecurity prevailing at that time, five suspected-trachoma-endemic health districts (Bol and Ngouri in Lac Region, Nokou in Kanem Region, Mandelia in Chari Baguirmi Region and Bardaï in Tibesti Region) could not be surveyed.

Survey design, field team training and certification, fieldwork, and data handling were conducted according to the systems and methodologies of the Global Trachoma Mapping Project (GTMP).20–23 Each of the 40 secure health districts was generally surveyed as a single evaluation unit (EU), though six health districts with populations (estimated using 2009 population census data24 and a mean annual population growth rate of 3.6%) significantly larger than the standard 100,000–250,000-person EU were divided into two EUs each, resulting in a total of 46 independent EUs.

Village-level population estimates were provided by the Division of Health & Information Systems. According to the 2009 census,24 the proportion of the population aged 1–9 years was 36% and rural households had a mean of 5.3 residents. The estimated sample size requirement per EU was based on an expected TF prevalence of 10% in children aged 1–9 years, a design effect of 2.65, and a desire to be 95% confident of estimating the TF prevalence with ± 3% absolute precision.22 The resulting sample size (n = 1019) was increased by 20% to account for non-response; this resulted in a total of 649 households being required per EU.

Using a two-stage cluster-sampling design, 22 clusters (villages or neighbourhoods) were systematically selected in each EU using probability-proportional-to-population-size sampling. In each cluster, compact segment sampling25,26 was then used to select 30 households. All residents over the age of 12 months who had resided for at least six months in selected households were eligible for enrolment.

A survey team consisted of a grader (ophthalmic technician), a recorder (high school graduate at ease with Android smart phones and fluent in major local languages), a local facilitator and a driver. Members of the survey team underwent standardized GTMP training, using version 2 of the system.27 Candidate graders were assessed after training, and only those obtaining a kappa of ≥ 0.7 for diagnosis of TF in an inter-grader agreement test with a GTMP-certified grader trainer were accepted as survey graders. Trachoma grading was done according to the WHO simplified grading system.4 Graders used 2.5× magnifying binocular loupes and sunlight illumination to examine consenting residents. In eyes diagnosed as having trichiasis, the presence or absence of trachomatous conjunctival scarring28,29 was not recorded, so we are unable to confirm that trichiasis cases detected were due to trachoma; consequently, we refer here to the prevalence of trichiasis instead of the prevalence of trachomatous trichiasis. Each survey team was trained to ask questions relating to access to water and sanitation at each selected household.27

All data were captured electronically, through the Open Data Kit-based Android phone application purpose-built for the GTMP. Once saved, data were sent to and stored on the GTMP Cloud-based secure server, then cleaned and analyzed.22 For each survey cluster, the proportion of 1–9-year-old children with TF was adjusted by age in one-year age bands, while the proportion of ≥ 15-year-olds with trichiasis was adjusted by age and gender in five-year age bands; age and gender data from the 2009 Chad census were used as the reference population for this purpose.24 For each EU, the primary outcome of interest was the age-adjusted prevalence of TF in 1–9-year-olds; intended secondary outcomes were the age- and gender-adjusted prevalence of trichiasis in ≥ 15-year-olds, and household-level access to water and sanitation. Confidence intervals for TF and trichiasis prevalence estimates were calculated by bootstrapping sets of 22 adjusted cluster-level proportions for each sign, with replacement, over 10,000 replicates, and taking the 2.5th and 97.5th centiles of the ordered results. Additional gender-specific age-adjusted estimates of trichiasis prevalence, with 95% confidence intervals, were calculated in analogous fashion. The ratio of trichiasis prevalence in females to that in males in each EU was also determined, and linear regression modelling (Stata 11, College Station TX, USA) used to generate an intra-class correlation coefficient, to assess the association between EU-level trichiasis prevalence and ratio of gender-specific prevalences.

Ethical clearance was obtained from the Chadian Ethical Committee for Applied Research, led by the Ministry of Higher Education; and from the London School of Hygiene & Tropical Medicine (6319). The examination procedure was explained to each eligible adult in the local language and verbal consent for enrolment and examination was obtained. For eligible children, verbal consent was obtained from a parent or guardian. Individuals with active trachoma were offered 1% tetracycline ointment for application into the conjunctival sac twice-daily for six weeks. Individuals with trichiasis were offered management by a surgeon.

Results

Fieldwork was undertaken from May 2014 to November 2015. At a subsequent field team meeting, it emerged that fieldworkers had considered their main task to be the acquisition of information on TF and trichiasis. Contrary to the survey protocol and the standard GTMP training package, in some villages, questions about access to water and sanitation had not been systematically asked in each selected household. Rather, information had been collected from the head of the village at the beginning of the day and those answers used for each household visited. Although this shortcut was not employed by all teams, it cast doubt on the accuracy of our water and sanitation data, and we do not include those data in this manuscript. Data cleaning revealed inconsistency in definitions of EU and district boundaries. In particular, in three health districts (Pala, Béré & Kélo, and Donomanga & Laï) that had each been split into two EUs, GPS data revealed considerable overlap between clusters that had ostensibly been drawn from separate EUs. Data from these pairs of within-health-district EUs were therefore combined to re-constitute health-district-level EUs; the numbers of clusters finally included in each EU are shown in Table 2. GPS data30 were not received at all from a high proportion of households mapped in both of Moundou’s two EUs; those that had GPS data were geolocated in a pattern inconsistent with known administrative divisions. For that reason, the data from Moundou did not pass GTMP quality control, and the outputs were, as expected, rejected by the health ministry. We therefore present data here from what became a total of 41 surveys.

Table 2.

Numbers of children and adults enumerated and examined, by evaluation unit, Global Trachoma Mapping Project, Chad, 2014–2015.

Region Evaluation unit (label in Figures 1 and 2) Population Number of clusters enrolled Number of households enrolled Number of 1–9-year-olds enumerated Number of 1–9-year-olds
absent		 Number of 1–9-year-olds refused Number of 1–9-year- olds examined Number of ≥ 15-year-olds enumerated Number of ≥ 15-year-olds absent Number of ≥ 15-year-olds refused Number of ≥ 15-year-olds examined
Batha Ati (1) 274,781 22 659 1324 0 0 1324 1050 0 0 1050
Batha Oum Hadjer (2) 233,223 22 651 1143 2 0 1141 840 1 3 836
Batha Yao (3) 143,616 22 649 1319 1 1 1317 935 0 9 926
Logone Occidental Laokassy (4) 105,630 22 674 1479 0 0 1479 1127 1 0 1126
Logone Occidental Bénoye (5) 215,959 22 671 1240 1 0 1239 1111 0 0 1111
Logone Oriental Doba (6) 276,045 22 656 1145 0 0 1145 1072 0 2 1070
Logone Oriental Béboto (7) 138,022 23 683 1162 0 0 1162 1238 1 0 1237
Logone Oriental Bébédjia (8) 156,476 22 653 987 0 9 978 946 1 3 942
Logone Oriental Goré (9) 188,824 22 662 1011 4 9 998 878 2 4 872
Logone Oriental Bessao (10) 225,366 22 656 1127 1 6 1120 937 0 3 934
Mayo Kebbi Est Bongor (11) 249,290 22 621 1263 2 0 1261 863 2 0 861
Mayo Kebbi Est Gounou Gaya (12) 289,412 22 1217 2742 0 0 2742 1233 0 0 1233
Mayo Kebbi Est Guélengdeng (13) 124,644 22 672 984 0 1 983 911 0 1 910
Mayo Kebbi Est Fianga (14) 287,664 22 641 1331 0 0 1331 967 0 0 967
Mayo Kebbi Ouest Palaa (15) 418,505 44a 1759 4023 0 0 4023 2617 0 1 2616
Mayo Kebbi Ouest Léré (16) 280,168 23 685 1053 0 0 1053 1452 0 0 1452
Tandjilé Béré & Kéloa (17) 349,348 42 1284 3156 1 0 3155 2327 0 1 2326
Tandjilé Donomanga & Laïa (18) 261,505 44 a 1363 2843 0 0 2843 2592 0 0 2592
Moyen Chari Sarh (19) 394,519 22 655 956 0 0 956 943 0 1 942
Moyen Chari Danamadji (20) 130,286 22 648 972 0 0 972 1028 0 0 1028
Moyen Chari Kyabé (21) 214,913 22 655 1041 0 0 1041 900 0 1 899
N’Djamena Suburbs (22) 1 228 352 22 660 1355 0 0 1355 1183 0 1 1182
Borkou Faya (23) 115,710 22 623 1080 1 1 1078 1097 2 4 1091
Ennédi (West & East) Fada & Bahai (24) 214,646 21 591 1095 0 3 1092 927 0 3 924
Bahr El Gazel Moussoro (25) 322,533 22 650 1074 0 4 1070 844 0 7 837
Chari Baguirmi Massenya (26) 186,922 22 646 956 0 0 956 890 1 0 889
Chari Baguirmi Dourbali (27) 193,305 22 660 1007 0 0 1007 964 0 2 962
Chari Baguirmi Bousso (28) 195,242 22 657 1061 1 0 1060 975 0 1 974
Hadjer Lamis Massakory (29) 232,731 22 655 1122 0 5 1117 878 0 5 873
Hadjer Lamis Massaguet (30) 191,689 22 671 1330 0 0 1330 1213 0 0 1213
Kanem Mao-1 (31) 165,060 20 608 1066 0 0 1066 853 0 0 853
Kanem Mao-2 (32) 152,363 24 729 1297 0 0 1297 987 3 0 984
Mandoul Koumra (33) 242,159 22 661 1384 0 0 1384 1289 0 0 1289
Mandoul Goundi (34) 181,620 22 658 1206 0 0 1206 1178 0 0 1178
Mandoul Moïssala (35) 242,834 22 660 1248 0 0 1248 1147 0 0 1147
Mandoul Bédjondo (36) 121,081 22 659 1097 0 0 1097 818 0 0 818
Wadi Fira Biltine (37) 301,263 22 659 1259 0 0 1259 1430 0 0 1430
Wadi Fira Guéréda (38) 192,918 22 657 1124 0 0 1124 1649 0 0 1649
Wadi Fira Iriba (39) 117,753 22 659 1304 0 0 1304 1481 1 0 1480
Hadjer Lamis Bokoro-1 (40) 127,661 22 665 1400 0 0 1400 1395 0 0 1395
Hadjer Lamis Bokoro-2 (41) 143,958 22 668 1449 0 0 1449 1363 1 0 1362
Total 8,599,644 967 29,910 56,215 14 39 56,162 48,528 16 52 48,460
Open in a new tab

aIntended to be mapped as two EUs (please see text)

In total, 104,705 people were enrolled and 104,584 (99%) examined in 29,239 households recruited from 967 clusters (Table 2). There were almost equal numbers of 1–9-year-olds (n = 55,885) and ≥ 15-year-olds (n = 48,699) examined. While the sampling process was designed to facilitate examination of at least 1,019 children in each EU, the survey teams in five EUs did not reach this target, with the lowest number of 1–9-year-olds examined in an EU being 956; reports from the field indicated that in many locations, households had fewer resident children than expected.

The adjusted TF prevalence in 1–9-year-old children was ≥ 5% (above the WHO threshold for elimination31) in 16 (39%) of the 41 EUs. Five EUs (12%) had TF prevalence estimates of 10–29.9%, and 11 EUs (27%) had TF prevalence estimates of 5–9.9% (Table 3, Figure 1).

Table 3.

Prevalence of trachomatous inflammation—follicular (TF) in 1–9-year-olds, prevalence of trichiasis in ≥ 15-year-olds, backlog of trichiasis cases and number of trichiasis cases needing management to reach the WHO elimination threshold, by evaluation unit, Global Trachoma Mapping Project, Chad, 2014–2015.

Region Evaluation unit (label in Figures 1 and 2) TF prevalencea, % (95% CI) Trichiasis prevalenceb, % (95% CI) Estimated backlog of trichiasis casesc Estimated number of trichiasis cases needing management to reach WHO elimination threshold
Batha Ati (1) 10.9 (7.3–14.7) 0.57 (0.25–0.98) 774 499
Batha Oum Hadjer (2) 8.6 (6.0–11.7) 0.55 (0.25–0.96) 634 401
Batha Yao (3) 5.4 (3.4–6.8) 0.30 (0.07–0.64) 213 69
Logone Occidental Laokassy (4) 2.5 (1.5–3.5) 0.29 (0.07–0.62) 151 45
Logone Occidental Bénoye (5) 1.9 (1.1–2.9) 0.02 (0.0–0.05) 21 0
Logone Oriental Doba (6) 5.9 (3.2–9.6) 0.14 (0.0–0.38) 191 0
Logone Oriental Béboto (7) 3.4 (1.4–6.3) 0.15 (0.04–0.30) 102 0
Logone Oriental Bébédjia (8) 1.3 (0.4–2.4) 0.36 (0.10–0.64) 278 122
Logone Oriental Goré (9) 3.4 (1.9–5.2) 0.72 (0.32–1.27 672 483
Logone Oriental Bessao (10) 3.9 (2.0–5.9) 0.92 (0.26–1.66) 1024 799
Mayo Kebbi Est Bongor (11) 2.7 (1.5–4.0) 0.34 (0.0–0.93) 419 170
Mayo Kebbi Est Gounou Gaya (12) 2.4 (1.7–3.0) 0.08 (0.0–0.20) 114 0
Mayo Kebbi Est Guélengdeng (13) 6.0 (2.9–10.1) 0.59 0.23–1.09) 363 238
Mayo Kebbi Est Fianga (14) 1.8 (0.6–3.5) 0.14 (0.0–0.33) 199 0
Mayo Kebbi Ouest Pala (15) 6.6 (5.1–8.4) 0.20 (0.07–0.36) 413 0
Mayo Kebbi Ouest Léré (16) 4.5 (2.9–5.6) 0.47 (0.09–1.08) 650 370
Tandjilé Béré & Kélo (17) 0.1 (0.0–0.3) 0.06 (0.0–0.16) 104 0
Tandjilé Donomanga & Laï (18) 0.2 (0.0–0.5) 0.50 (0.17–0.94) 646 384
Moyen Chari Sarh (19) 5.1 (3.1–7.4) 0.33 (0.13–0.51) 643 248
Moyen Chari Danamadji (20) 4.3 (2.2–6.2) 0.17 (0.04–0.36) 109 0
Moyen Chari Kyabé (21) 7.3 (5.4–8.9) 0.93 (0.44–1.49) 987 772
N’Djamena Suburbs (22) 4.2 (2.5–6.6) 0.13 (0.0–0.31) 789 0
Borkou Faya (23) 10.1 (4.0–19.0) 1.21 (0.31–2.01) 692 576
Ennédi (West & East) Fada & Bahai (24) 8.5 (4.3–14.2) 0.18 (0.0–0.41) 191 0
Bahr El Gazel Moussoro (25) 0.0 (0.0–0.0) 0.60 (0.15–1.25) 956 633
Chari Baguirmi Massenya (26) 4.1 (1.6–6.8) 0.17 (0.04–0.32) 157 0
Chari Baguirmi Dourbali (27) 4.9 (2.2–7.6) 0.52 (0.22–0.92) 497 304
Chari Baguirmi Bousso (28) 7.9 (4.1–14.3) 0.39 (0.15–0.59) 376 181
Hadjer Lamis Massakory (29) 0.1 (0.0–0.2) 0.45 (0.09–0.83) 517 284
Hadjer Lamis Massaguet (30) 0.4 (0.1–0.9) 0.19 (0.05–0.35) 180 0
Kanem Mao-1 (31) 23.3 (19.0–29.4) 0.44 (0.11–0.84) 358 193
Kanem Mao-2 (32) 16.2 (12.7–20.2) 0.23 (0.02–0.50) 173 21
Mandoul Koumra (33) 3.5 (1.8–5.9) 0.87 (0.39–1.32) 1041 799
Mandoul Goundi (34) 11.4 (8.6–15.0) 0.55 (0.31–0.95) 493 311
Mandoul Moïssala (35) 9.8 (7.0–13.8) 0.69 (0.29–1.06) 828 585
Mandoul Bédjondo (36) 0.0 (0.0–0.0) 0.20 (0.0–0.48) 120 0
Wadi Fira Biltine (37) 6.9 (5.4–8.8) 1.30 (0.79–1.86) 1935 1634
Wadi Fira Guéréda (38) 0.3 (0.0–0.6) 0.37 (0.11–0.74) 353 160
Wadi Fira Iriba (39) 1.7 (0.8–2.9) 0.31 (0.09–0.60) 180 62
Hadjer Lamis Bokoro-1 (40) 1.1 (0.2–2.4) 0.55 (0.11–1.19) 347 219
Hadjer Lamis Bokoro-2 (41) 2.0 (0.5–4.8) 0.16 (0.03–0.34) 114 0
Total       19,004 10,562
Open in a new tab

aAdjusted for age in 1-year age bands (see text)

bAdjusted for gender and age in 5-year age bands (see text)

cBacklog calculated as prevalence × population × proportion of population aged ≥ 15 years (0.494)

dNumber of cases needing management to reach WHO elimination threshold calculated as backlog – (0.002 × population aged ≥ 15 years)

CI, confidence interval

Figure 1.

Figure 1.

Open in a new tab

Prevalence of trachomatous inflammation—follicular (TF) in 1–9-year-olds, Global Trachoma Mapping Project, Chad, 2014–2015. Evaluation units are labelled with numbers; the key is found in Tables 2, 3 and 4.

In 12 EUs (29%), the age- and gender-adjusted trichiasis prevalence was below the WHO elimination threshold31 of 0.2% in ≥ 15-year-olds (Table 3, Figure 2). In the remaining 29 EUs, trichiasis prevalence was ≥ 0.2%. Two EUs had trichiasis prevalence estimates of > 1%. The estimated number of trichiasis patients requiring management to achieve elimination of trichiasis as a public health problem at the time of conclusion of the surveys was 10,562 (Table 3).

Figure 2.

Figure 2.

Open in a new tab

Prevalence of trichiasis in ≥ 15-year-olds, Global Trachoma Mapping Project, Chad, 2014–2015. Evaluation units are labelled with numbers; the key is found in Tables 2, 3 and 4.

Analysis of gender-specific age-adjusted trichiasis prevalence estimates revealed mean EU-level prevalences of 0.55% in women and 0.28% in men; in 31 (76%) of the 41 EUs, the prevalence of trichiasis was higher in women than men (Table 4). There were five EUs in which none of the men examined had trichiasis. The mean ratio of prevalence in women to that in men (excluding the five EUs in which prevalence in men was 0) was 1.70 (SE = 0.53) in the EUs below the WHO elimination threshold, and 2.31 (SE = 0.48) in the EUs above the WHO elimination threshold. A higher prevalence of trichiasis was associated with a greater excess of disease in women (correlation coefficient = 250, SE = 114, p = 0.03).

Table 4.

Prevalence of trichiasis in males and females aged ≥ 15 years, by evaluation unit, Global Trachoma Mapping Project, Chad, 2014–2015.

Region Evaluation unit Trichiasis prevalence in all ≥ 15-year-oldsa, % (95% CI) Trichiasis prevalence in ♀ ≥ 15-year-oldsb, % (95% CI) Trichiasis prevalence in ♂ ≥ 15-year-oldsb, % (95% CI) Ratio of prevalence in ♀: prevalence in ♂s
Batha Ati (1) 0.57 (0.25–0.98) 0.62 (0.17–1.24) 0.50 (0.0–1.19) 1.2
Batha Oum Hadjer (2) 0.55 (0.25–0.96) 0.54 (0.17–1.13) 0.56 (0.09–1.30) 1.0
Batha Yao (3) 0.30 (0.07–0.64) 0.57 (0.14–1.23) 0 (0.0–0.0) NA
Logone Occidental Laokassy (4) 0.29 (0.07–0.62) 0.33 (0.05–0.70) 0.25 (0.0–0.77) 1.3
Logone Occidental Bénoye (5) 0.02 (0.0–0.05) 0.03 (0.0–0.10) 0 (0.0–0.0) NA
Logone Oriental Doba (6) 0.14 (0.0–0.38) 0.08 (0.0–0.24) 0.21 (0.0–0.63) 0.4
Logone Oriental Béboto (7) 0.15 (0.04–0.30) 0.08 (0.0–0.19) 0.22 (0.0–0.54) 0.4
Logone Oriental Bébédjia (8) 0.36 (0.10–0.64) 0.30 (0.06–0.52) 0.41 (0.0–1.04) 0.7
Logone Oriental Goré (9) 0.72 (0.32–1.27 1.38 (0.62–2.42) 0 (0.0–0.0) NA
Logone Oriental Bessao (10) 0.92 (0.26–1.66) 1.02 (0.25–1.70) 0.81 (0.0–2.30) 1.6
Mayo Kebbi Est Bongor (11) 0.34 (0.0–0.93) 0.65 (0.0–1.76) 0 (0.0–0.0) NA
Mayo Kebbi Est Gounou Gaya (12) 0.08 (0.0–0.20) 0.07 (0.0–0.17) 0.10 (0.0–0.29) 0.7
Mayo Kebbi Est Guélengdeng (13) 0.59 0.23–1.09) 0.89 (0.33–1.67) 0.26 (0.0–0.69) 3.4
Mayo Kebbi Est Fianga (14) 0.14 (0.0–0.33) 0.28 (0.0–0.62) 0 (0.0–0.0) NA
Mayo Kebbi Ouest Pala (15) 0.20 (0.07–0.36) 0.12 (0.0–0.28) 0.27 (0.05–0.59) 0.4
Mayo Kebbi Ouest Léré (16) 0.47 (0.09–1.08) 0.70 (0.16–1.58) 0.21 (0.0–0.56) 3.3
Tandjilé Béré & Kélo (17) 0.06 (0.0–0.16) 0.07 (0.0–0.20) 0.06 (0.0–0.17) 1.2
Tandjilé Donomanga & Laï (18) 0.50 (0.17–0.94) 0.81 (0.22–1.63) 0.16 (0.0–0.43) 5.2
Moyen Chari Sarh (19) 0.33 (0.13–0.51) 0.30 (0.13–0.54) 0.37 (0.0–0.69) 0.8
Moyen Chari Danamadji (20) 0.17 (0.04–0.36) 0.15 (0.0–0.34) 0.18 (0.0–0.55) 0.8
Moyen Chari Kyabé (21) 0.93 (0.44–1.49) 1.17 (0.61–1.63) 0.67 (0.0–1.53) 1.7
N’Djamena Suburbs (22) 0.13 (0.0–0.31) 0.18 (0.0–0.47) 0.08 (0.0–0.20) 2.4
Borkou Faya (23) 1.21 (0.31–2.01) 2.15 (0.55–3.63) 0.19 (0.0–0.37) 11.6
Ennédi (West & East) Fada & Bahai (24) 0.18 (0.0–0.41) 0.27 (0.0–0.63) 0.09 (0.0–0.26) 3.2
Bahr El Gazel Moussoro (25) 0.60 (0.15–1.25) 0.91 (0.15–2.16) 0.27 (0.0–0.53) 3.4
Chari Baguirmi Massenya (26) 0.17 (0.04–0.32) 0.18 (0.0–0.42) 0.15 (0.0–0.40) 1.2
Chari Baguirmi Dourbali (27) 0.52 (0.22–0.92) 0.68 (0.23–1.31) 0.35 (0.0–0.95) 1.9
Chari Baguirmi Bousso (28) 0.39 (0.15–0.59) 0.41 (0.08–0.67) 0.36 (0.08–0.73) 1.2
Hadjer Lamis Massakory (29) 0.45 (0.09–0.83) 0.55 (0.09–1.00) 0.35 (0.0–0.89) 1.6
Hadjer Lamis Massaguet (30) 0.19 (0.05–0.35) 0.26 (0.03–0.58) 0.12 (0.0–0.25) 2.1
Kanem Mao-1 (31) 0.44 (0.11–0.84) 0.51 (0.12–0.89) 0.37 (0.0–1.10) 1.4
Kanem Mao-2 (32) 0.23 (0.02–0.50) 0.16 (0.0–0.39) 0.30 (0.0–0.77) 0.5
Mandoul Koumra (33) 0.87 (0.39–1.32) 0.88 (0.28–1.57) 0.86 (0.14–1.58) 1.0
Mandoul Goundi (34) 0.55 (0.31–0.95) 0.73 (0.32–1.34) 0.35 (0.09–0.68) 2.1
Mandoul Moïssala (35) 0.69 (0.29–1.06) 0.83 (0.23–1.36) 0.54 (0.08–1.25) 1.6
Mandoul Bédjondo (36) 0.20 (0.0–0.48) 0.30 (0.0–0.69) 0.08 (0.0–0.25) 3.6
Wadi Fira Biltine (37) 1.30 (0.79–1.86) 1.64 (0.87–2.83) 0.90 (0.24–1.52) 1.8
Wadi Fira Guéréda (38) 0.37 (0.11–0.74) 0.60 (0.18–1.23) 0.13 (0.0–0.38) 4.8
Wadi Fira Iriba (39) 0.31 (0.09–0.60) 0.40 (0.09–0.88) 0.20 (0.0–0.54) 2.0
Hadjer Lamis Bokoro-1 (40) 0.55 (0.11–1.19) 0.44 (0.16–0.83) 0.67 (0.0–1.76) 0.7
Hadjer Lamis Bokoro-2 (41) 0.16 (0.03–0.34) 0.26 (0.0–0.61) 0.04 (0.0–0.13) 6.2
Open in a new tab

aAdjusted for gender and age in 5-year age bands (see text)

bAdjusted for age in 5-year age bands (see text)

CI, confidence interval; NA, not applicable

Discussion

The results of these and previous surveys demonstrate that trachoma is a public health problem in Chad. To move towards elimination of trachoma as a public health problem, AFE interventions should be implemented for at least three years before re-survey for the approximately 887,000 people in the five EUs in which TF prevalence was ≥ 10%, and for at least one year before re-survey for the nearly 2.8 million people in the 11 EUs in which TF prevalence was 5–9.9%. Although we are unable to report our own data on access to water and sanitation, 2017 data released by the Chad Government and UNICEF suggest that region-level proportions of the population with access to potable water are as low as 12% (Ennedi-Est), and that outside N’Djamena, region-level rates of open defecation range from 61 to 93%. These conditions are associated with high risk of active trachoma,32,33 highlighting the need for the F&E components of the SAFE strategy here.

The TF prevalence estimates from these GTMP-supported surveys are considerably lower than those of previous surveys completed in Chad.13–15 There are a number of possible explanations for this. When surveys were first planned here, it would have been logical to choose to start in districts with higher expected burdens of trachoma – where, in other words, eye health professionals were already aware of cases. There may also, or alternatively, have been a temporal decline in the prevalence of active trachoma in the intervening period,34–37 with older surveys reflecting C. trachomatis transmission intensities38 occurring before more recent improvements in access to water, sanitation and health care. The GTMP’s emphasis on standardization of trachoma grading (including grader training and qualification based on examination of real people, rather than projected images20) may also have contributed.

Trichiasis is widespread in Chad (Figure 2), with more than two-thirds of EUs surveyed in 2014–2015 having trichiasis prevalence estimates above the WHO elimination threshold. Establishing a public health-level response to trichiasis throughout the widely dispersed communities in these EUs will require considerable capacity building for delivery of high-quality trichiasis surgery and programme management, as well as community-based efforts to generate awareness and encourage uptake of services.39,40 The excess burden of trichiasis among females (Table 4), also noted elsewhere,25,41,42 compels us to ensure that such efforts particularly serve women. Experience in other countries can inform strategies to improve use of eye care services by women.43,44 The association noted here between higher prevalence of trichiasis and greater ratio of trichiasis prevalence in women to trichiasis prevalence in men cannot be explained from our data alone. We note that this was not a pre-specified hypothesis of the current work, and suggest only that further investigation is indicated.

Our work has a number of limitations. First, in five EUs, we did not quite reach the estimated sample size requirement. We report confidence intervals here, however, which facilitates objective assessment of the likely repeatability of our estimates. In future surveys in Chad, the sampling approach will be revised slightly to reflect the smaller-than-expected mean number of children encountered per household. Second, we recruited these marginally low numbers of examinees despite what was apparently an extraordinarily high enrolment rate: 99% of enumerated residents. We wonder whether field teams, fearing criticism for incomplete enrolment, may have failed to register absentees: anecdotally, this occurred in other constituent projects of the GTMP, but obtaining definitive proof was difficult.20 Third, this survey work was commenced prior to the inclusion of examination for trachomatous conjunctival scarring (TS4) in standard GTMP protocols,45 as later recommended by a global scientific meeting.29 It is therefore likely that some of the trichiasis cases included in our prevalence estimates were due to conditions other than trachoma28,29; this may explain part of the association between the overall prevalence of trichiasis and the ratio of gender-specific prevalence estimates. We also did not ask about previous management of trichiasis, so the trichiasis prevalence estimates reported here include both cases known and unknown to the health system.19 These refinements can be helpful in influencing whether or not public-health-level interventions are needed against trichiasis.46 Fourth, as noted in the results section, three EU pairs were combined at the data cleaning stage; the main implication of this is that the resulting EU populations (like that for N’Djamena suburbs) are larger than the recommended 100,000–250,000 people.19 Fifth, as also already noted, data from two EUs in Moundou, Logone Occidental Region, could not be approved due to missing GPS data; as a consequence, results from this EU are not included in the current report. Sixth, because household-level questions were not used as set out in the survey protocol, we are unable to report data on access to water and sanitation. Though unfortunate, as much as this situation reveals a weakness in one part of fieldwork execution, it also demonstrates strength in fieldwork supervision.

Subsequent to completing these surveys, in addition to expanding SAFE interventions, the Ministry of Health commenced planning to re-map Moundou as well as to undertake mapping in some of, but not all, the EUs in which surveys were not attempted in 2014–2015. Undertaking those surveys will contribute to the completion of nationwide mapping of suspected-trachoma-endemic areas of Chad, and help chart a course towards national elimination of trachoma as a public health problem.47

Appendix

The Global Trachoma Mapping Project Investigators are: Agatha Aboe (1,11), Liknaw Adamu (4), Wondu Alemayehu (4,5), Menbere Alemu (4), Neal D. E. Alexander (9), Berhanu Bero (4), Simon J. Brooker (1,6), Simon Bush (7,8), Brian K. Chu (2,9), Paul Courtright (1,3,4,7,11), Michael Dejene (3), Paul M. Emerson (1,6,7), Rebecca M. Flueckiger (2), Allen Foster (1,7), Solomon Gadisa (4), Katherine Gass (6,9), Teshome Gebre (4), Zelalem Habtamu (4), Danny Haddad (1,6,7,8), Erik Harvey (1,6,10), Dominic Haslam (8), Khumbo Kalua (5), Amir B. Kello (4,5), Jonathan D. King (6,10,11), Richard Le Mesurier (4,7), Susan Lewallen (4,11), Thomas M. Lietman (10), Chad MacArthur (6,11), Colin Macleod (3,9), Silvio P. Mariotti (7,11), Anna Massey (8), Els Mathieu (6,11), Siobhain McCullagh (8), Addis Mekasha (4), Tom Millar (4,8), Caleb Mpyet (3,5), Beatriz Muñoz (6,9), Jeremiah Ngondi (1,3,6,11), Stephanie Ogden (6), Alex Pavluck (2,4,10), Joseph Pearce (10), Serge Resnikoff (1), Virginia Sarah (4), Boubacar Sarr (5), Alemayehu Sisay (4), Jennifer L. Smith (11), Anthony W. Solomon (1,2,3,4,5,6,7,8,9,10,11), Jo Thomson (4), Sheila K. West (1,10,11), Rebecca Willis (2,9).

Key: (1) Advisory Committee, (2) Information Technology, Geographical Information Systems, and Data Processing, (3) Epidemiological Support, (4) Ethiopia Pilot Team, (5) Master Grader Trainers, (6) Methodologies Working Group, (7) Prioritisation Working Group, (8) Proposal Development, Finances and Logistics, (9) Statistics and Data Analysis, (10) Tools Working Group, (11) Training Working Group.

Funding Statement

This study was funded by the Global Trachoma Mapping Project (GTMP) grant from the United Kingdom’s Department for International Development (ARIES: 203145) to Sightsavers, which led a consortium of non-governmental organizations and academic institutions to support health ministries to complete baseline trachoma mapping worldwide, and by the United States Agency for International Development (USAID) through the ENVISION project implemented by RTI International under cooperative agreement number AID-OAA-A-11-00048. The GTMP was also funded by USAID through the END in Asia project implemented by FHI360 under cooperative agreement number OAA-A-10-00051. A committee established in March 2012 to examine issues surrounding completion of global trachoma mapping was initially funded by a grant from Pfizer to the International Trachoma Initiative. AWS was a Wellcome Trust Intermediate Clinical Fellow (098521) at the London School of Hygiene & Tropical Medicine, and is now a staff member of the World Health Organization. The authors alone are responsible for the views expressed in this article and they do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated. None of the funders had any role in project design, in project implementation or analysis or interpretation of data, in the decisions on where, how or when to publish in the peer reviewed press, or in preparation of the manuscript.

Disclosure Statement

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

References

  • 1.Flaxman SR, Bourne RRA, Resnikoff S, et al. Global causes of blindness and distance vision impairment 1990-2020: a systematic review and meta-analysis. Lancet Glob Health. 2017. doi: 10.1016/S2214-109X(17)30393-5. [DOI] [PubMed] [Google Scholar]
  • 2.Mabey DC, Solomon AW, Foster A.. Trachoma. Lancet. 2003;362(9379):223–229. doi: 10.1016/S0140-6736(03)13914-1. [DOI] [PubMed] [Google Scholar]
  • 3.Solomon AW, Holland MJ, Burton MJ, et al. Strategies for control of trachoma: observational study with quantitative PCR. Lancet. 2003;362(9379):198–204. doi: 10.1016/S0140-6736(03)13909-8. [DOI] [PubMed] [Google Scholar]
  • 4.Thylefors B, Dawson CR, Jones BR, West SK, Taylor HR. A simple system for the assessment of trachoma and its complications. Bull World Health Organ. 1987;65:477–483. [PMC free article] [PubMed] [Google Scholar]
  • 5.Grayston JT, Wang SP, Yeh LJ, Kuo CC. Importance of reinfection in the pathogenesis of trachoma. Rev. Infect. Dis. 1985;7:717–725. [DOI] [PubMed] [Google Scholar]
  • 6.Gambhir M, Basanez MG, Burton MJ, et al. The development of an age-structured model for trachoma transmission dynamics, pathogenesis and control. PLoS Negl Trop Dis. 2009;3(6):e462. doi: 10.1371/journal.pntd.0000462. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.West SK, Munoz B, Mkocha H, Hsieh YH, Lynch MC. Progression of active trachoma to scarring in a cohort of Tanzanian children. Ophthalmic Epidemiol. 2001;8:137–144. [DOI] [PubMed] [Google Scholar]
  • 8.Francis V, Turner V. Achieving Community Support for Trachoma Control (WHO/PBL/93.36). Geneva: World Health Organization; 1993. [Google Scholar]
  • 9.Kuper H, Solomon AW, Buchan J, Zondervan M, Foster A, Mabey D. A critical review of the SAFE strategy for the prevention of blinding trachoma. Lancet Infect Dis. 2003;3:372–381. [DOI] [PubMed] [Google Scholar]
  • 10.Solomon AW, Zondervan M, Kuper H, Buchan JC, Mabey DCW, Foster A. Trachoma Control: A Guide for Programme Managers. Geneva: World Health Organization; 2006. [Google Scholar]
  • 11.Solomon AW, Peeling RW, Foster A, Mabey DC. Diagnosis and assessment of trachoma. Clin Microbiol Rev. 2004;17(4):982–1011. doi: 10.1128/CMR.17.4.982-1011.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Resnikoff S, Lamarque D. Compte rendu d’enquete: sondage sur la trachome et les cecites a Mao et Bol (Tchad). Bull OCEAC. 1985;71:47–56. [Google Scholar]
  • 13.Resnikoff S. Compte rendu d’enquête sur la situation ophtalmologique dans les préfectures du Biltine et du Ouaddaï. Bull OCEAC. 1987;79:109–115. [Google Scholar]
  • 14.Madani MO, Huguet P, Mariotti SP, et al. [Trachoma in Chad: results of an epidemiological survey]. Sante. 2003;13(1):9–15. [PubMed] [Google Scholar]
  • 15.Dézoumbé D, Djada DA, Négrel AD. Resultats preliminaires de quatre enquetes epidemiologiques de prevalence du trachome (2001-2005): Note de synthèse. N’Djamena: Programme National de Lutte Contre la Cécité, Ministère de la Santé; 2005. [Google Scholar]
  • 16.Dawson CR, Jones BR, Tarizzo ML. Guide to Trachoma Control in Programmes for the Prevention of Blindness. Geneva: World Health Organization; 1981. [Google Scholar]
  • 17.Solomon AW, Emerson PM, Resnikoff S. Trachoma then and now: update on mapping and control. Community Eye Health. 2017;30:90–91. [PMC free article] [PubMed] [Google Scholar]
  • 18.Smith JL, Haddad D, Polack S, et al. Mapping the global distribution of trachoma: why an updated atlas is needed. PLoS Negl Trop Dis. 2011;5(6):e973. doi: 10.1371/journal.pntd.0001370. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.World Health Organization Report of the 3rd global scientific meeting on trachoma, Johns Hopkins University, Baltimore, MA, 19-20 July 2010 (WHO/PBD/2.10). Geneva: World Health Organization; 2010. [Google Scholar]
  • 20.Solomon AW, Willis R, Pavluck AL, et al. Quality assurance and quality control in the global trachoma mapping project. Am J Trop Med Hyg. 2018;99(4):858–863. doi: 10.4269/ajtmh.18-0082. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Solomon AW, Kurylo E. The global trachoma mapping project. Community Eye Health. 2014;27:18. [PMC free article] [PubMed] [Google Scholar]
  • 22.Solomon AW, Pavluck A, Courtright P, et al. The global trachoma mapping project: methodology of a 34-country population-based study. Ophthalmic Epidemiol. 2015;22(3):214–225. doi: 10.3109/09286586.2015.1037401. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Mpyet C, Kello AB, Solomon AW. Global elimination of trachoma by 2020: A work in progress. Ophthalmic Epidemiol. 2015;22(3):148–150. doi: 10.3109/09286586.2015.1045987. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.République du Tchad Recensement général de la population. N’Djamena: Institut national de la statistique, des études économiques et démographiques; 2009. [Google Scholar]
  • 25.Bero B, Macleod C, Alemayehu W, et al. Prevalence of and risk factors for trachoma in Oromia regional state of Ethiopia: results of 79 population-based prevalence surveys conducted with the global trachoma mapping project. Ophthalmic Epidemiol. 2016;23(6):392–405. doi: 10.1080/09286586.2016.1243717. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Phiri I, Manangazira P, Macleod CK, et al. The burden of and risk factors for trachoma in selected districts of Zimbabwe: results of 16 population-based prevalence surveys. Ophthalmic Epidemiol. 2018;25(Sup 1):181–191. doi: 10.1080/09286586.2017.1298823. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Courtright P, Gass K, Lewallen S, et al. Global Trachoma Mapping Project: Training for Mapping of Trachoma (Version 2). London: International Coalition for Trachoma Control; 2013. http://www.trachomacoalition.org/node/357]. [Google Scholar]
  • 28.World Health Organization Strategic and Technical Advisory Group on Neglected Tropical Diseases Technical Consultation on Trachoma Surveillance. September 11−12, 2014, Task Force for Global Health, Decatur, USA (WHO/HTM/NTD/2015.02). Geneva: World Health Organization; 2015. [Google Scholar]
  • 29.World Health Organization Alliance for the Global Elimination of Trachoma by 2020 Second Global Scientific Meeting on Trachomatous Trichiasis. Cape Town, 4-6 November 2015 (WHO/HTM/NTD/2016.5). Geneva: World Health Organization; 2016. [Google Scholar]
  • 30.Polack SR, Solomon AW, Alexander ND, et al. The household distribution of trachoma in a Tanzanian village: an application of GIS to the study of trachoma. Trans R Soc Trop Med Hyg. 2005;99(3):218–225. doi: 10.1016/j.trstmh.2004.06.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.World Health Organization Validation of Elimination of Trachoma as a Public Health Problem (WHO/HTM/NTD/2016.8). Geneva: World Health Organization; 2016. [Google Scholar]
  • 32.Garn JV, Boisson S, Willis R, et al. Sanitation and water supply coverage thresholds associated with active trachoma: modeling cross-sectional data from 13 countries. PLoS Negl Trop Dis. 2018;12(1):e0006110. doi: 10.1371/journal.pntd.0006110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Oswald WE, Stewart AE, Kramer MR, et al. Active trachoma and community use of sanitation, Ethiopia. Bull World Health Organ. 2017;95(4):250–260. doi: 10.2471/BLT.16.177758. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Jha H, Chaudary JS, Bhatta R, et al. Disappearance of trachoma from Western Nepal. Clin Infect Dis. 2002;35(6):765–768. doi: 10.1086/342298. [DOI] [PubMed] [Google Scholar]
  • 35.Chidambaram JD, Alemayehu W, Melese M, et al. Effect of a single mass antibiotic distribution on the prevalence of infectious trachoma. Jama. 2006;295(10):1142–1146. doi: 10.1001/jama.295.10.1142. [DOI] [PubMed] [Google Scholar]
  • 36.Dolin PJ, Faal H, Johnson GJ, et al. Reduction of trachoma in a sub-Saharan village in absence of a disease control programme. Lancet. 1997;349(9064):1511–1512. [DOI] [PubMed] [Google Scholar]
  • 37.Dolin PJ, Faal H, Johnson GJ, Ajewole J, Mohamed AA, Lee PS. Trachoma in The Gambia. Br J Ophthalmol. 1998;82:930–933. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Migchelsen SJ, Sepulveda N, Martin DL, et al. Serology reflects a decline in the prevalence of trachoma in two regions of The Gambia. Sci Rep. 2017;7(1):15040. doi: 10.1038/s41598-017-15056-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Burton M, Solomon A. What’s new in trichiasis surgery? Community Eye Health. 2004;17:52–53. [PMC free article] [PubMed] [Google Scholar]
  • 40.Gupta KM, Harding JC, Othman MS, Merbs SL, Gower EW. Why do patients refuse trichiasis surgery? Lessons and an education initiative from Mtwara Region, Tanzania. PLoS Negl Trop Dis. 2018;12(6):e0006464. doi: 10.1371/journal.pntd.0006464. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Elshafie BE, Osman KH, Macleod C, et al. The epidemiology of trachoma in Darfur states and Khartoum state, sudan: results of 32 population-based prevalence surveys. Ophthalmic Epidemiol. 2016;23(6):381–391. doi: 10.1080/09286586.2016.1243718. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Cromwell EA, Courtright P, King JD, Rotondo LA, Ngondi J, Emerson PM. The excess burden of trachomatous trichiasis in women: a systematic review and meta-analysis. Trans R Soc Trop Med Hyg. 2009;103(10):985–992. doi: 10.1016/j.trstmh.2009.03.012. [DOI] [PubMed] [Google Scholar]
  • 43.Mousa A, Courtright P, Kazanjian A, Bassett K. A community-based eye care intervention in Southern Egypt: impact on trachomatous trichiasis surgical coverage. Middle East Afr J Ophthalmol. 2015;22(4):478–483. doi: 10.4103/0974-9233.167808. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.West S, Nguyen MP, Mkocha H, et al. Gender equity and trichiasis surgery in the Vietnam and Tanzania national trachoma control programmes. Br J Ophthalmol. 2004;88(11):1368–1371. doi: 10.1136/bjo.2004.041657. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Courtright P, Gass K, Lewallen S, et al. Global Trachoma Mapping Project: Training for Mapping of Trachoma (Version 3). London: International Coalition for Trachoma Control; 2014. http://www.trachomacoalition.org/node/122]. [Google Scholar]
  • 46.Khan AA, Florea VV, Hussain A, et al. Prevalence of Trachoma in Pakistan: results of 42 population-based prevalence surveys from the global trachoma mapping project. Ophthalmic Epidemiol. 2018. In preparation. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Courtright P, Rotondo LA, MacArthur C, et al. Strengthening the links between mapping, planning and global engagement for disease elimination: lessons learnt from trachoma. Br J Ophthalmol. 2018;102(10):1324–1327. doi: 10.1136/bjophthalmol-2018-312476. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Ophthalmic Epidemiology are provided here courtesy of Taylor & Francis

RESOURCES