Kenya tuberculosis prevalence survey 2016: Challenges and opportunities of ending TB in Kenya

Masini, Enos; Sitienei, Joseph; Ong’ang’o, Jane Rahedi; Mungai, Brenda; Kamene, Maureen; Wambugu, Jesse; Kipruto, Hillary; Manduku, Veronica; Mburu, Josephine W.; Nyaboke, Drusilla; Ngari, Faith; Omesa, Eunice; Omale, Newton; Mwirigi, Nkirote; Okallo, Geoffrey; Njoroge, Janice; Githiomi, M M; Mwangi, Mike; Kirathe, Dickson; Kiplimo, Richard; Ndombi, Amos; Odeny, Lazarus; Mailu, Eunice; Kandie, Timothy; Maina, Maurice; Kasera, Kadondi; Mulama, Beatrice; Mugi, Beatrice; Weyenga, Herman

doi:10.1371/journal.pone.0209098

Cited by 96 publications

(129 citation statements)

References 7 publications

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“…Low levels of suspicion of clinicians as well as difficulties in obtaining adequate samples for confirmation are also reported as a challenge in EPTB diagnosis [21]. In addition, some of the reasons for higher proportion of PTB in Serbia compared with EU/EEA countries could be due to low HIV prevalence in Serbia [22] and to the dominant proportion of men among TB patients as there is evidence that the incidence of EPTB is likely to be higher among women than men [23].…”

Section: Discussionmentioning

confidence: 99%

“…Patients with severe forms of extra-pulmonary disease may be less likely to become lost, because they are likely to be in closer contact with the healthcare provider and may be hospitalised [34]. Weaknesses in the health system, such as lack of updated clinical guidelines, non-compliance of healthcare professionals with the guidelines, interruptions in drug supply or poor training, supervision and organisation of TB programmes, have also been identified as factors contributing to the poor management of patients, resulting in treatment interruptions and loss to follow-up [2,23].…”

Section: Discussionmentioning

confidence: 99%

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Trends in tuberculosis notification and mortality and factors associated with treatment outcomes in Serbia, 2005 to 2015

et al. 2020

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Background: Previously a country with medium tuberculosis (TB) burden, Serbia almost reached a low TB burden during the period 2005 to 2015. Aim: The aim of this study was to analyse the trends in notification rates and treatment success rates as well as to identify predictors of treatment outcomes. Methods: We performed a trend analysis and logistic regression analysis of 17,441 TB cases registered from 2005 to 2015 in all health facilities in Serbia, to identify predictors of treatment success, loss to follow-up and mortality. Results: From 2005 to 2015, TB notification rate and mortality in Serbia decreased but treatment success remained below the global target. Loss to follow-up was associated with retreatment (odds ratio (OR) = 2.38; 95% confidence interval (CI): 2.08-2.77),

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Trends in tuberculosis notification and mortality and factors associated with treatment outcomes in Serbia, 2005 to 2015

et al. 2020

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“…Kenya suffers from the dual epidemics ranking 4 th and 15 th globally in the high disease burden for HIV and TB respectively [29][30][31]. The high HIV prevalence in Kenya is the major driver of TB related mortality and TB prevalence is also the leading cause of HIV related mortality [31].…”

Section: Motivation Of the Studymentioning

confidence: 99%

Bayesian hierarchical modeling of joint spatiotemporal risk patterns for Human Immunodeficiency Virus (HIV) and Tuberculosis (TB) in Kenya

Otiende¹,

Achia

Mwambi

2020

Preprint

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The spatiotemporal modeling of multiple diseases simultaneously is a recent extension that advances the space-time analysis to model multiple related diseases simultaneously. This approach strengthens inferences by borrowing information between related diseases. Numerous research contributions to spatiotemporal modeling approaches exhibit their strengths differently with increasing complexity. However, contributions that combine spatiotemporal approaches to modeling of multiple diseases simultaneously are not so common. We present a full Bayesian hierarchical spatio-temporal approach to the joint modeling of Human Immunodeficiency Virus and Tuberculosis incidences in Kenya. Using case notification data for the period 2012 - 2017, we estimated the model parameters and determined the joint spatial patterns and temporal variations. Our model included specific and shared spatial and temporal effects. The specific random effects allowed for departures from the shared patterns for the different diseases. The space-time interaction term characterized the underlying spatial patterns with every temporal fluctuation. We assumed the shared random effects to be the structured effects and the disease-specific random effects to be unstructured effects. We detected the spatial congruence in the distribution of Tuberculosis and Human Immunodeficiency Virus in approximately 29 counties around the western, central and southern regions of Kenya. The distribution of the shared relative risks had minimal difference with the Human Immunodeficiency Virus disease-specific relative risk whereas that of Tuberculosis presented many more counties as high-risk areas. The flexibility and informative outputs of Bayesian Hierarchical Models enabled us to identify the similarities and differences in the distribution of the relative risks associated with each disease. Estimating the Human Immunodeficiency Virus and Tuberculosis shared relative risks provide additional insights towards collaborative monitoring of the diseases and control efforts.

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“…This means that nearly half of the number of people with TB disease are undetected and not on treatment and so they are considered as missing TB persons. (13) Tuberculosis (TB) contacts are people who have close contact with patients with infectious TB, because they are at high risk for infection (and in line with the End TB strategy), TB contacts should be investigated systematically and actively for TB infection and disease. (3)Contact investigation is important in finding contacts who have Tuberculosis (TB) disease so that they can be given treatment and stop further transmission .…”

Section: Introductionmentioning

confidence: 99%

Community health volunteers’ contribution to Tuberculosis patients notified to National Tuberculosis program through contact investigation in Kenya

Abongo

Ulo²,

Karanja³

2020

Preprint

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Background: Contact investigation is important in finding contacts of people who have Tuberculosis (TB) disease so that they can be given treatment and stop further transmission. The main objective of this study was to assess the contribution of community health volunteers (CHVs) to the number of TB patients notified to the National program in Kenya through household contact screening and referral of persons with TB signs and symptoms to the facilities for further investigation.Methods: This was a retrospective desk review of project reports submitted to Amref Health Africa in Kenya by the sub recipients implementing activities in the 33 counties with Case Notification Rate (CNR) of less 175/100,000 and Treatment Success Rate (TRS) of less than 88% as per the National strategic plan 2015-2018. Data for this study covered a time period between January and December 2016. Data on the notified TB patients was obtained from the National Tuberculosis Information Basic Unit (TIBU). The study population included all the TB index cases whose households were visited by CHVs for contact screening. Data was recorded into excel spreadsheets where descriptive analysis was done, proportions calculated and summarized in a table.Results: Community health volunteers visited a total of 26,307 TB patients (index cases) in their households for contact screening. A total of 44,617 household members were screened for TB with 43,012 (96.40%) coming from households of bacteriologically confirmed TB patients and 1,606 (3.60%) from households of children under 5 years. The proportion of the persons referred in relation to the number screened was 19.6 % for those over 5 years and 21.9 % from under 5 years with almost the same percentages for male and female at 19.2% and 19.7 % respectively. The percentage of (TB) cases identified through tracing of contacts in these counties improved to 10% (5,456) of the 54,913 cases notified to the National TB Program while the percentage of notified TB cases, all forms contributed though community referrals improved to 6 % (3,365)Conclusions: This study showed that in the 33 counties of Global Fund TB project implementation the percentage of TB cases identified through tracing of contacts improved from 6% to 10% while the percentage of notified TB cases; all forms contributed through community referrals improved from 4% to 8%. Community health volunteers can play an effective role in household contact screening and referrals for identification of TB.

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Kenya tuberculosis prevalence survey 2016: Challenges and opportunities of ending TB in Kenya

Cited by 96 publications

References 7 publications

Trends in tuberculosis notification and mortality and factors associated with treatment outcomes in Serbia, 2005 to 2015

Trends in tuberculosis notification and mortality and factors associated with treatment outcomes in Serbia, 2005 to 2015

Bayesian hierarchical modeling of joint spatiotemporal risk patterns for Human Immunodeficiency Virus (HIV) and Tuberculosis (TB) in Kenya

Community health volunteers’ contribution to Tuberculosis patients notified to National Tuberculosis program through contact investigation in Kenya

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