Use of Lot Quality Assurance Sampling to Ascertain Levels of Drug Resistant Tuberculosis in Western Kenya

Unbiased antimicrobial resistance prevalence estimates through population-based surveillance

BACKGROUND

Current antimicrobial resistance surveillance (AMR) is mainly laboratory-based. This approach can have inherent biases given the potential for selective specimen submission for microbiological analysis, and for its inability to map antibiotic susceptibility test results to a clinical syndrome.

OBJECTIVES

To discuss the need for population-based surveillance of AMR, and highlight the pros and cons of threshold surveys.

SOURCES

Studies on methodology for AMR surveillance published in the last 10 years, obtained through a PubMed search on antimicrobial resistance (all fields) and surveillance/method (MeSH term).

CONTENT

We discuss the use of threshold surveys to overcome the challenge of sample size in population-bases AMR surveys, which are a suitable approach in both low- and high-resource settings.

IMPLICATION

Scale up in the use of population-based threshold survey on the prevalence of AMR will provide necessary information to triangulate the data from routinely-reported laboratory-based AMR surveillance at the local, national and global level.

Mixed Methods Lot Quality Assurance Sampling: A novel, rapid methodology to inform equity focused maternal health programming in rural Rajasthan, India

India has experienced a significant increase in facility-based delivery (FBD) coverage and reduction in maternal mortality. Nevertheless, India continues to have high levels of maternal health inequity. Improving equity requires data collection methods that can produce a better contextual understanding of how vulnerable populations access and interact with the health care system at a local level. While large population-level surveys are valuable, they are resource intensive and often lack the contextual specificity and timeliness to be useful for local health programming. Qualitative methods can be resource intensive and may lack generalizability. We describe an innovative mixed-methods application of Large Country-Lot Quality Assurance Sampling (LC-LQAS) that provides local coverage data and qualitative insights for both FBD and antenatal care (ANC) in a low-cost and timely manner that is useful for health care providers working in specific contexts. LC-LQAS is a version of LQAS that combines LQAS for local level classification with multistage cluster sampling to obtain precise regional or national coverage estimates. We integrated qualitative questions to uncover mothers' experiences accessing maternal health care in the rural district of Sri Ganganagar, Rajasthan, India. We interviewed 313 recently delivered, low-income women in 18 subdistricts. All respondents participated in both qualitative and quantitative components. All subdistricts were classified as having high FBD coverage with the upper threshold set at 85%, suggesting that improved coverage has extended to vulnerable women. However, only two subdistricts were classified as high ANC coverage with the upper threshold set at 40%. Qualitative data revealed a severe lack of agency among respondents and that household norms of care seeking influenced uptake of ANC and FBD. We additionally report on implementation outcomes (acceptability, feasibility, appropriateness, effectiveness, fidelity, and cost) and how study results informed the programs of a local health non-profit.

Evaluation of neonatal mortality data completeness and accuracy in Ghana

Background

Cause-specific mortality data are required to set interventions to reduce neonatal mortality. However, in many developing countries, these data are either lacking or of low quality. We assessed the completeness and accuracy of cause of death (COD) data for neonates in Ghana to assess their usability for monitoring the effectiveness of health system interventions aimed at improving neonatal survival.

Methods

A lot quality assurance sampling survey was conducted in 20 hospitals in the public sector across four regions of Ghana. Institutional neonatal deaths (IND) occurring from 2014 through 2017 were divided into lots, defined as neonatal deaths occurring in a selected facility in a calendar year. A total of 52 eligible lots were selected: 10 from Ashanti region, and 14 each from Brong Ahafo, Eastern and Volta region. Nine lots were from 2014, 11 from 2015 and 16 each were from 2016 and 2017. The cause of death (COD) of 20 IND per lot were abstracted from admission and discharge (A&D) registers and validated against the COD recorded in death certificates, clinician’s notes or neonatal death audit reports for consistency. With the error threshold set at 5%, ≥ 17 correctly matched diagnoses in a sample of 20 deaths would make the lot accurate for COD diagnosis. Completeness of COD data was measured by calculating the proportion of IND that had death certificates completed.

Results

Nineteen out of 52 eligible (36.5%) lots had accurate COD diagnoses recorded in their A&D registers. The regional distribution of lots with accurate COD data is as follows: Ashanti (4, 21.2%), Brong Ahafo (7, 36.8%), Eastern (4, 21.1%) and Volta (4, 21.1%). Majority (9, 47.4%) of lots with accurate data were from 2016, followed by 2015 and 2017 with four (21.1%) lots. Two (10.5%) lots had accurate COD data in 2014. Only 22% (239/1040) of sampled IND had completed death certificates.

Conclusion

Death certificates were not reliably completed for IND in a sample of health facilities in Ghana from 2014 through 2017. The accuracy of cause-specific mortality data recorded in A&D registers was also below the desired target. Thus, recorded IND data in public sector health facilities in Ghana are not valid enough for decision-making or planning. Periodic data quality assessments can determine the magnitude of the data quality concerns and guide site-specific improvements in mortality data management.

Pulmonary tuberculosis screening in anti-retroviral treated adults living with HIV in Kenya

Background

People living with HIV (PLHIV) who reside in high tuberculosis burden settings remain at risk for tuberculosis disease despite treatment with anti-retroviral therapy and isoniazid preventive therapy (IPT). The performance of the World Health Organization (WHO) symptom screen for tuberculosis in PLHIV receiving anti-retroviral therapy is sub-optimal and alternative screening strategies are needed.

Methods

We enrolled HIV-positive adults into a prospective study in western Kenya. Individuals who were IPT-naïve or had completed IPT > 6 months prior to enrollment were eligible. We evaluated tuberculosis prevalence overall and by IPT status. We assessed the accuracy of the WHO symptom screen, GeneXpert MTB/RIF (Xpert), and candidate biomarkers including C-reactive protein (CRP), hemoglobin, erythrocyte sedimentation rate (ESR), and monocyte-to-lymphocyte ratio for identifying pulmonary tuberculosis. Some participants were evaluated at 6 months post-enrollment for tuberculosis.

Results

The study included 383 PLHIV, of whom > 99% were on antiretrovirals and 88% had received IPT, completed a median of 1.1 years (IQR 0.8–1.55) prior to enrollment. The prevalence of pulmonary tuberculosis at enrollment was 1.3% (n = 5, 95% CI 0.4–3.0%): 4.3% (0.5–14.5%) among IPT-naïve and 0.9% (0.2–2.6%) among IPT-treated participants. The sensitivity of the WHO symptom screen was 0% (0–52%) and specificity 87% (83–90%). Xpert and candidate biomarkers had poor to moderate sensitivity; the most accurate biomarker was CRP ≥ 3.3 mg/L (sensitivity 80% (28–100) and specificity 72% (67–77)). Six months after enrollment, the incidence rate of pulmonary tuberculosis following IPT completion was 0.84 per 100 person-years (95% CI, 0.31–2.23).

Conclusions

In Kenyan PLHIV treated with IPT, tuberculosis prevalence was low at a median of 1.4 years after IPT completion. WHO symptoms screening, Xpert, and candidate biomarkers were insensitive for identifying pulmonary tuberculosis in antiretroviral-treated PLHIV.

Rethinking Antimicrobial Resistance Surveillance: A Role for Lot Quality Assurance Sampling

Global surveillance of antimicrobial resistance (AMR) is a key component of the 68th World Health Assembly Global Action Plan on AMR. Laboratory-based surveillance is inherently biased and lacks local relevance due to aggregation of data. We assessed the feasibility, sensitivity, and affordability of a population-based AMR survey using lot quality assurance sampling (LQAS), which classifies a population as having a high or low prevalence of AMR based on a priori defined criteria. Three studies were carried out in Medan and Bandung, Indonesia, between April 2014 and June 2017. LQAS classifications for 15 antibiotics were compared with AMR estimates from a conventional population-based survey, with an assessment of the cost of a single LQAS classification using microcosting methodology, among patients suspected of urinary tract infection at 11 sites in Indonesia. The sensitivity of LQAS was above 98%. The approach detected local variation in the prevalence of AMR across sites. Time to reach LQAS results ranged from 47 to 138 days. The average cost of an LQAS classification in a single facility was US$466. The findings indicate that LQAS-based AMR survey is a feasible, sensitive, and affordable strategy for population-based AMR surveys, providing essential data to inform local empirical treatment guidelines and antimicrobial stewardship efforts.

Prevalence of Drug Resistance Mycobacterium Tuberculosis among Patients Seen in Coast Provincial General Hospital, Mombasa, Kenya

Background

Although prevention and control of spread of multi-drug resistant tuberculosis strains is a global challenge, there is paucity of data on the prevalence of DR-TB in patients diagnosed with TB in referral hospitals in Kenya. The present study assessed patients’ characteristics and prevalence of drug resistant TB in sputa smear positive TB patients presenting to Coast Provincial General Hospital (CPGH) in Mombasa, Kenya.

Methods

Drug resistance was evaluated in 258 randomly selected sputa smear TB positive cases between the periods of November 2011 to February 2012 at the CPGH-Mombasa. Basic demographic data was obtained using administered questionnaires, and clinical history extracted from the files. For laboratory analyses, 2mls of sputum was obtained, decontaminated and subjected to mycobacteria DNA analyses. Detection of first line drug resistance genes was done using MDRTDR plus kit. This was followed with random selection of 83 cases for second line drug resistance genes testing using Genotype MDRTBsl probe assay kit (HAINS Lifesciences, GmbH, Germany), in which ethambutol mutation probes were included. The data was then analyzed using SPSS statistical package version 19.0.

Results

Male to female ratio was 1:2. Age range was 9 to 75 years, with median of 30 years. New treatment cases constituted 253(98%), among which seven turned out to be PTB negative, and further grouped as 4 (1.6%) PTB negative and 3(1.1%) NTM. 237(91.7%) new cases were fully susceptible to INH and RIF. The remaining, 8 (3.1%) and 1(0.4%) had mono- resistance to INH and RIF, respectively. All the retreatment cases were fully susceptible to the first line drugs. HIV positivity was found in 48 (18.6%) cases, of which 46(17.8%) were co-infected with TB. Of these, 44 (17.1%) showed full susceptibility to TB drugs, while 2 (0.8%) were INH resistant. For the second line drugs, one case each showed mono resistance to both and FQ. Also, one case each showed drug cross poly resistance to both ETH and FQ, with second line injectable antibiotics. However, no significant statistical correlation was established between TB and resistance to the second line drugs p = 0.855.

Conclusion

The findings of this study showed the existence of resistance to both first and second line anti-tubercular drugs, but no MDR-TB and XDR-TB was detected among patients attending TB clinic at CPGH using molecular techniques.