Tropical Medicine and International Health
doi:10.1111/tmi.12558
volume 20 no 10 pp 1396–1402 october 2015
Tuberculosis case detection in Nigeria, the unfinished agenda Joshua Obasanya1, Saddiq T. Abdurrahman2, Olanrewaju Oladimeji3,4, Lovett Lawson3, Russell Dacombe4, Nkem Chukwueme1, Tubi Abiola1, Gidado Mustapha5, Christophe Sola6, Jose Dominguez7 and Luis E. Cuevas4 1 2 3 4 5 6 7
National Tuberculosis and Leprosy Control Programme of Nigeria, Abuja, Nigeria Federal Capital Territory Abuja Tuberculosis And Leprosy Control Programme, Abuja, Nigeria Zankli Medical Centre, Abuja, Nigeria Liverpool School of Tropical Medicine, UK TB Care, KNCV / TB CARE I, Abuja, Nigeria Microbiology Department, Universite Paris-Sud, Orsay, France Servei de Microbiologia, Hospital Universitari Germans Trias i Pujol, Badalona, Spain
Abstract
objective Underdetection of TB is a major problem in sub-Saharan Africa. WHO recommends countries should have at least 1 laboratory per 100 000 population. However, this recommendation is not evidence based. methods We analysed surveillance data of the Nigerian National TB Control Programme (20082012) to describe TB case detection rates, their geographical distribution and their association with the density of diagnostic laboratories and HIV prevalence. results The median CDR was 17.7 (range 4.7–75.8%) in 2008, increasing to 28.6% (range 10.6–72.4%) in 2012 (P < 0.01). The CDR2012 was associated with the 2008 baseline; however, states with CDR2008 < 30% had larger increases than states with CDR2008 > 30. There were 990 laboratories in 2008 and 1453 in 2012 (46.7% increase, range by state 3% to +118). The state CDR2012 could be predicted by the laboratory density (P < 0.001), but was not associated with HIV prevalence or the proportion of smear-positive cases. CDR2012 and laboratory density were correlated among states having < and > than 1 laboratory per 100 000 population. conclusion There are large variations in laboratory density and CDR across the Nigerian states. The CDR is associated with the laboratory density. A much larger number of diagnostic centres are needed. It is likely that a laboratory density above the recommended WHO guideline would result in even higher case detection, and this ratio should be considered a minimum threshold. keywords tuberculosis, surveillance, diagnostic centres, case detection, HIV
Introduction Tuberculosis (TB) is a major public health problem, and the poor detection of cases by TB control programmes remains one of the main barriers for control. Up to one-third of the cases estimated to occur each year are never reported to the national TB control programmes (NTPs) worldwide. In Nigeria, despite the National TB and Leprosy Control Programme (NTBLCP) reporting 94 604 cases in 2012, this number only represents 51% of the cases estimated to have occurred in the country for that year[1]. Better case detection in the most populous country in Africa is therefore urgently needed[2]. Most NTPs rely on sputum smear microscopy for TB diagnosis and decentralise the diagnostic centres as much as possible to primary healthcare centres to 1396
improve service accessibility. WHO recommends this decentralisation, and it is recommended that NTPs provide at least one TB diagnostic centre per 100 000 population[3]. This ratio is based on the maximum workload that a laboratory could handle to provide good quality smear microscopy and is based on expert opinion assuming that the ideal number of smears examined per microscopist per day should range between 2 and 20 per day[4]. Although this recommendation has stand for many years, the premise for these calculations is not ideal, as service provision should ideally reflect the number of centres that are needed to ensure service accessibility. For example, in Nigeria, very few states achieve this ratio and patients have to travel to distant centres for diagnosis[5]. Nigeria also has one of the largest HIV-infected populations[6], with urban areas having higher prevalence
© 2015 John Wiley & Sons Ltd
Tropical Medicine and International Health
volume 20 no 10 pp 1396–1402 october 2015
J. Obasanya et al. Tuberculosis case detection in Nigeria, the unfinished agenda
than rural populations[7]. As HIV increases the risk of TB progression, it is likely to reduce the proportion of cases confirmed by smear microscopy. The association between the number and density of TB diagnostic centres and the proportion of estimated TB cases detected by the states has not been reported in Nigeria. We therefore analysed the geographical distribution of TB case detection in Nigeria and its association with the prevalence of HIV and with the number of TB diagnostic centres by state during a 5-year period of standardised data collection.
Methods Setting Nigeria had an estimated population of 154 million in 2009, with approximately 54% living in poverty[8]. The country is divided into 36 states plus the Federal Capital Territory (FCT). States are subdivided into 774 local government areas (LGAs) and geographically clustered into six geopolitical zones. The health system is structured along primary, secondary and tertiary levels roughly corresponding to the LGA, state and federal levels. The
Table 1 Demographic and TB surveillance data for 2008 and 2012
Population
Smear positive (%)
All TB
CDR % Change
State
2008
2012
2008
2012
2008
2012
2008
2012
Zamfara Abia Jigawa Sokoto Kebbi Osun Anambra Akwa Ibom Enugu Rivers Bayelsa Ekiti Imo Katsina Ondo Oyo Delta Edo Ogun Kwara Kogi Cross River Borno Taraba Yobe Niger Plateau Kano Ebonyi Kaduna Gombe Bauchi Benue Lagos Adamawa FCT Nasarawa
3 2 4 3 3 3 4 4 3 5 1 2 4 6 3 5 4 3 3 2 3 3 4 2 2 4 3 9
3 3 5 4 3 4 4 4 3 6 2 2 4 6 4 6 4 3 4 2 3 3 4 2 2 4 3 11
1.25 3.94 1.48 2.38 6.02 3.4 3.82 4.22 1.86 1.42 2.17 1.11 1.87 1.8 2.42 4.41 4.04 5.91 4.24 2.51 1.3 2.36 2.19 7.65 2.93 2.25 2.98 2.89 2.22 2.23 2.29 1.78 4.39 6.18 5.01 6.86 7.21
24.23 32.86 20.77 47.04 33.09 52.35 20.53 39.01 30.95 26.52 26.37 8.98 18.79 19.57 22.39 59.57 36.05 34.61 36.12 25.01 43.63 24.39 24.55 61.73 24.01 23.79 32.09 30.02 34.44 31.34 34.28 29.64 61.1 46.33 52.6 71.15 55.97
148 317 376 445 530 513 676 652 472 753 270 355 665 990 614 1265 921 807 883 237 86 795 1223 834 749 240 1702 3289 791 2274 888 1872 3229 4848 1681 894 1618
1185 1377 1533 2614 2052 2844 1461 2493 1660 2477 751 477 1261 2211 1405 6137 2799 1737 2271 995 2262 1781 2009 2919 1151 1532 2749 5328 1283 3749 1784 2595 5895 7712 3112 1983 2588
3 7 7 9 9 11 11 12 12 12 13 13 14 14 14 17 17 18 18 20 22 24 26 27 28 28 28 30 32 33 33 36 39 45 45 46 53
24 33 21 47 33 52 21 39 31 27 26 9 19 20 22 60 36 35 36 25 44 24 25 62 24 24 32 30 34 31 34 30 61 46 53 71 56
446 964 996 673 598 265 909 210 424 528 620 049 422 084 145 231 444 270 483 047 801 132 521 068 160 766 125 077 638 542 912 551 333 642 403 067 942 094 507 192 466 675 054 795 389 475 432 800 454 852 176 997 361 173 922 314 2298262 6 414 788 2 488 994 4 944 898 4 461 432 9 530 919 3 349 953 1 485 861 1 970 229
© 2015 John Wiley & Sons Ltd
854 039 350 570 141 305 370 875 828 953 047 565 944 318 634 769 851 027 130 576 013 840 818 798 652 138 848 428 068 241 610 804 845 431 804 958 407 642 803 283 876 078 415 556 907 857 720 106 744 762 670 286 758 116 094 106 2569679 7 172 353 2 782 936 5 528 874 4 988 313 10 656 488 3 745 571 1 661 336 2 202 906
21.18 26.22 14.07 38.04 23.63 41.58 9.06 27.49 19.1 14.21 13.54 3.99 4.68 5.2 7.93 42.59 18.84 16.8 17.96 4.74 21.45 0.72 1.13 35.09 3.58 3.93 4.12 0.24 2.24 1.88 0.89 6.44 22.37 1.64 7.44 25.38 3.44
1397
Tropical Medicine and International Health
volume 20 no 10 pp 1396–1402 october 2015
J. Obasanya et al. Tuberculosis case detection in Nigeria, the unfinished agenda
NTBLCP was established in 1989 and operates within the government health system. LGA health facilities provide TB treatment services; 65% of them have diagnostic laboratories[9]. Study design This is an analysis of the NTBLCP routine surveillance database comprising data collected from 2008 to 2012. Data in the NTBLCP database were collected from all government centres providing TB treatment and diagnostic services in the country and from all private facilities that have established agreements with the NTBLCP to participate in the programme activities. All reporting centres use dedicated TB registers and report using a purpose-built standardised electronic data entry forms with error-trapping routines. Reports prepared by the centres are sent to the LGA TB offices, where an LGA report is compiled by TB supervisors. LGAs submit their databases to the state offices, where they are further aggregated and
Map 1.Proportion of smear-positive cases reported (2012) Q1 (40 to
doi:10.1111/tmi.12558
volume 20 no 10 pp 1396–1402 october 2015
Tuberculosis case detection in Nigeria, the unfinished agenda Joshua Obasanya1, Saddiq T. Abdurrahman2, Olanrewaju Oladimeji3,4, Lovett Lawson3, Russell Dacombe4, Nkem Chukwueme1, Tubi Abiola1, Gidado Mustapha5, Christophe Sola6, Jose Dominguez7 and Luis E. Cuevas4 1 2 3 4 5 6 7
National Tuberculosis and Leprosy Control Programme of Nigeria, Abuja, Nigeria Federal Capital Territory Abuja Tuberculosis And Leprosy Control Programme, Abuja, Nigeria Zankli Medical Centre, Abuja, Nigeria Liverpool School of Tropical Medicine, UK TB Care, KNCV / TB CARE I, Abuja, Nigeria Microbiology Department, Universite Paris-Sud, Orsay, France Servei de Microbiologia, Hospital Universitari Germans Trias i Pujol, Badalona, Spain
Abstract
objective Underdetection of TB is a major problem in sub-Saharan Africa. WHO recommends countries should have at least 1 laboratory per 100 000 population. However, this recommendation is not evidence based. methods We analysed surveillance data of the Nigerian National TB Control Programme (20082012) to describe TB case detection rates, their geographical distribution and their association with the density of diagnostic laboratories and HIV prevalence. results The median CDR was 17.7 (range 4.7–75.8%) in 2008, increasing to 28.6% (range 10.6–72.4%) in 2012 (P < 0.01). The CDR2012 was associated with the 2008 baseline; however, states with CDR2008 < 30% had larger increases than states with CDR2008 > 30. There were 990 laboratories in 2008 and 1453 in 2012 (46.7% increase, range by state 3% to +118). The state CDR2012 could be predicted by the laboratory density (P < 0.001), but was not associated with HIV prevalence or the proportion of smear-positive cases. CDR2012 and laboratory density were correlated among states having < and > than 1 laboratory per 100 000 population. conclusion There are large variations in laboratory density and CDR across the Nigerian states. The CDR is associated with the laboratory density. A much larger number of diagnostic centres are needed. It is likely that a laboratory density above the recommended WHO guideline would result in even higher case detection, and this ratio should be considered a minimum threshold. keywords tuberculosis, surveillance, diagnostic centres, case detection, HIV
Introduction Tuberculosis (TB) is a major public health problem, and the poor detection of cases by TB control programmes remains one of the main barriers for control. Up to one-third of the cases estimated to occur each year are never reported to the national TB control programmes (NTPs) worldwide. In Nigeria, despite the National TB and Leprosy Control Programme (NTBLCP) reporting 94 604 cases in 2012, this number only represents 51% of the cases estimated to have occurred in the country for that year[1]. Better case detection in the most populous country in Africa is therefore urgently needed[2]. Most NTPs rely on sputum smear microscopy for TB diagnosis and decentralise the diagnostic centres as much as possible to primary healthcare centres to 1396
improve service accessibility. WHO recommends this decentralisation, and it is recommended that NTPs provide at least one TB diagnostic centre per 100 000 population[3]. This ratio is based on the maximum workload that a laboratory could handle to provide good quality smear microscopy and is based on expert opinion assuming that the ideal number of smears examined per microscopist per day should range between 2 and 20 per day[4]. Although this recommendation has stand for many years, the premise for these calculations is not ideal, as service provision should ideally reflect the number of centres that are needed to ensure service accessibility. For example, in Nigeria, very few states achieve this ratio and patients have to travel to distant centres for diagnosis[5]. Nigeria also has one of the largest HIV-infected populations[6], with urban areas having higher prevalence
© 2015 John Wiley & Sons Ltd
Tropical Medicine and International Health
volume 20 no 10 pp 1396–1402 october 2015
J. Obasanya et al. Tuberculosis case detection in Nigeria, the unfinished agenda
than rural populations[7]. As HIV increases the risk of TB progression, it is likely to reduce the proportion of cases confirmed by smear microscopy. The association between the number and density of TB diagnostic centres and the proportion of estimated TB cases detected by the states has not been reported in Nigeria. We therefore analysed the geographical distribution of TB case detection in Nigeria and its association with the prevalence of HIV and with the number of TB diagnostic centres by state during a 5-year period of standardised data collection.
Methods Setting Nigeria had an estimated population of 154 million in 2009, with approximately 54% living in poverty[8]. The country is divided into 36 states plus the Federal Capital Territory (FCT). States are subdivided into 774 local government areas (LGAs) and geographically clustered into six geopolitical zones. The health system is structured along primary, secondary and tertiary levels roughly corresponding to the LGA, state and federal levels. The
Table 1 Demographic and TB surveillance data for 2008 and 2012
Population
Smear positive (%)
All TB
CDR % Change
State
2008
2012
2008
2012
2008
2012
2008
2012
Zamfara Abia Jigawa Sokoto Kebbi Osun Anambra Akwa Ibom Enugu Rivers Bayelsa Ekiti Imo Katsina Ondo Oyo Delta Edo Ogun Kwara Kogi Cross River Borno Taraba Yobe Niger Plateau Kano Ebonyi Kaduna Gombe Bauchi Benue Lagos Adamawa FCT Nasarawa
3 2 4 3 3 3 4 4 3 5 1 2 4 6 3 5 4 3 3 2 3 3 4 2 2 4 3 9
3 3 5 4 3 4 4 4 3 6 2 2 4 6 4 6 4 3 4 2 3 3 4 2 2 4 3 11
1.25 3.94 1.48 2.38 6.02 3.4 3.82 4.22 1.86 1.42 2.17 1.11 1.87 1.8 2.42 4.41 4.04 5.91 4.24 2.51 1.3 2.36 2.19 7.65 2.93 2.25 2.98 2.89 2.22 2.23 2.29 1.78 4.39 6.18 5.01 6.86 7.21
24.23 32.86 20.77 47.04 33.09 52.35 20.53 39.01 30.95 26.52 26.37 8.98 18.79 19.57 22.39 59.57 36.05 34.61 36.12 25.01 43.63 24.39 24.55 61.73 24.01 23.79 32.09 30.02 34.44 31.34 34.28 29.64 61.1 46.33 52.6 71.15 55.97
148 317 376 445 530 513 676 652 472 753 270 355 665 990 614 1265 921 807 883 237 86 795 1223 834 749 240 1702 3289 791 2274 888 1872 3229 4848 1681 894 1618
1185 1377 1533 2614 2052 2844 1461 2493 1660 2477 751 477 1261 2211 1405 6137 2799 1737 2271 995 2262 1781 2009 2919 1151 1532 2749 5328 1283 3749 1784 2595 5895 7712 3112 1983 2588
3 7 7 9 9 11 11 12 12 12 13 13 14 14 14 17 17 18 18 20 22 24 26 27 28 28 28 30 32 33 33 36 39 45 45 46 53
24 33 21 47 33 52 21 39 31 27 26 9 19 20 22 60 36 35 36 25 44 24 25 62 24 24 32 30 34 31 34 30 61 46 53 71 56
446 964 996 673 598 265 909 210 424 528 620 049 422 084 145 231 444 270 483 047 801 132 521 068 160 766 125 077 638 542 912 551 333 642 403 067 942 094 507 192 466 675 054 795 389 475 432 800 454 852 176 997 361 173 922 314 2298262 6 414 788 2 488 994 4 944 898 4 461 432 9 530 919 3 349 953 1 485 861 1 970 229
© 2015 John Wiley & Sons Ltd
854 039 350 570 141 305 370 875 828 953 047 565 944 318 634 769 851 027 130 576 013 840 818 798 652 138 848 428 068 241 610 804 845 431 804 958 407 642 803 283 876 078 415 556 907 857 720 106 744 762 670 286 758 116 094 106 2569679 7 172 353 2 782 936 5 528 874 4 988 313 10 656 488 3 745 571 1 661 336 2 202 906
21.18 26.22 14.07 38.04 23.63 41.58 9.06 27.49 19.1 14.21 13.54 3.99 4.68 5.2 7.93 42.59 18.84 16.8 17.96 4.74 21.45 0.72 1.13 35.09 3.58 3.93 4.12 0.24 2.24 1.88 0.89 6.44 22.37 1.64 7.44 25.38 3.44
1397
Tropical Medicine and International Health
volume 20 no 10 pp 1396–1402 october 2015
J. Obasanya et al. Tuberculosis case detection in Nigeria, the unfinished agenda
NTBLCP was established in 1989 and operates within the government health system. LGA health facilities provide TB treatment services; 65% of them have diagnostic laboratories[9]. Study design This is an analysis of the NTBLCP routine surveillance database comprising data collected from 2008 to 2012. Data in the NTBLCP database were collected from all government centres providing TB treatment and diagnostic services in the country and from all private facilities that have established agreements with the NTBLCP to participate in the programme activities. All reporting centres use dedicated TB registers and report using a purpose-built standardised electronic data entry forms with error-trapping routines. Reports prepared by the centres are sent to the LGA TB offices, where an LGA report is compiled by TB supervisors. LGAs submit their databases to the state offices, where they are further aggregated and
Map 1.Proportion of smear-positive cases reported (2012) Q1 (40 to
