BACKGROUND: Understanding the magnitude and causes of mortality at national and sub-national levels for countries is critical in facilitating evidence-based prioritization of public health response. We provide comparable cause of death data from Kisumu County, a high HIV and malaria-endemic county in Kenya, and compared them with Kenya and low-and-middle income countries (LMICs). METHODS: We analyzed data from a mortuary-based study at two of the largest hospital mortuaries in Kisumu. Mortality data through 2019 for Kenya and all LMICs were downloaded from the Global Health Data Exchange. We provided age-standardized rates for comparisons of all-cause and cause-specific mortality rates, and distribution of deaths by demographics and Global Burden of Disease (GBD) classifications. RESULTS: The all-cause age-standardized mortality rate (SMR) was significantly higher in Kisumu compared to Kenya and LMICs (1118 vs. 659 vs. 547 per 100,000 population, respectively). Among women, the all-cause SMR in Kisumu was almost twice that of Kenya and double the LMICs rate (1150 vs. 606 vs. 518 per 100,000 population respectively). Among men, the all-cause SMR in Kisumu was approximately one and a half times higher than in Kenya and nearly double that of LMICs (1089 vs. 713 vs. 574 per 100,000 population). In Kisumu and LMICs non-communicable diseases accounted for most (48.0 and 58.1% respectively) deaths, while in Kenya infectious diseases accounted for the majority (49.9%) of deaths. From age 10, mortality rates increased with age across all geographies. The age-specific mortality rate among those under 1 in Kisumu was nearly twice that of Kenya and LMICs (6058 vs. 3157 and 3485 per 100,000 population, respectively). Mortality from injuries among men was at least one and half times that of women in all geographies. CONCLUSION: There is a notable difference in the patterns of mortality rates across the three geographical areas. The double burden of mortality from GBD Group I and Group II diseases with high infant mortality in Kisumu can guide prioritization of public health interventions in the county. This study demonstrates the importance of establishing reliable vital registry systems at sub-national levels as the mortality dynamics and trends are not homogeneous.

BACKGROUND: Lack of dependable morbidity and mortality data complicates efforts to measure the demographic or population-level impact of the global HIV/AIDS epidemic. Mortuary-based mortality surveillance can address gaps in vital statistics in low-resource settings by improving accuracy of measuring HIV-associated mortality and indicators of access to treatment services among decedents. This paper describes the process and considerations taken in conducting mortuary and hospital-based HIV mortality surveillance among decedents in Kenya. MAIN TEXT: We conducted HIV mortuary and hospital-based mortality surveillance at two of the largest mortuaries in Kisumu County, Kenya (April 16-July 12, 2019). Medical charts were reviewed for documentation of HIV status among eligible decedents. HIV testing was done on blood and oral fluid samples from decedents with undocumented HIV status and those whose medical records indicated HIV-negative test results > 3 months before death. A panel of experts established the cause of death according to the International Classification of Diseases, 10th Revision rules. Civil registry data for the year 2017 were abstracted and coded to corresponding ICD-10 codes. Of the 1004 decedents admitted to the two mortuaries during the study period, 49 (4.9%) were unavailable because they had been transferred to other facilities or dispatched for burial before enrolment. Of the 955 available decedents, 104 (10.9%) were ineligible for the study. Blood samples were collected from 659 (77.4%) decedents, and 654 (99.2%) were tested for HIV. Of the 564 decedents eligible for the OraQuick® validation sub-study, 154 were eligible for oral sample collection, and 132 (85.7%) matched pre- and post-embalming oral samples were collected and tested. Of the 851 eligible decedents, 241 (28.3%) had evidence of HIV infection: 119 had a diagnosis of HIV infection recorded in their patient files, and 122 had serological evidence of HIV infection. CONCLUSION: This study shows that in low-resource settings, conducting hospital and mortuary-based surveillance is feasible and can be an alternative source of mortality data when civil registry data are inadequate.

BACKGROUND: Estimating cause-related mortality among the dead is not common, yet for clinical and public health purposes, a lot can be learnt from the dead. HIV/AIDS accounted for the third most frequent cause of deaths in Kenya; 39.7 deaths per 100,000 population in 2019. OraQuick Rapid HIV-1/2 has previously been validated on oral fluid and implemented as a screening assay for HIV self-testing in Kenya among living subjects. We assessed the feasibility and diagnostic accuracy of OraQuick Rapid HIV-1/2 for HIV screening among decedents. METHODS: Trained morticians collected oral fluid from 132 preembalmed and postembalmed decedents aged >18 months at Jaramogi Oginga Odinga Teaching and Referral Hospital mortuary in western Kenya and tested for HIV using OraQuick Rapid HIV-1/2. Test results were compared with those obtained using the national HIV Testing Services algorithm on matched preembalming whole blood specimens as a gold standard (Determine HIV and First Response HIV 1-2-O). We calculated positive predictive values, negative predictive values, area under the curve, and sensitivity and specificity of OraQuick Rapid HIV-1/2 compared with the national HTS algorithm. RESULTS: OraQuick Rapid HIV-1/2 had similar sensitivity of 92.6% [95% confidence interval (CI): 75.7 to 99.1] on preembalmed and postembalmed samples compared with the gold standard. Specificity was 97.1% (95% CI: 91.9 to 99.4) and 95.2% (95% CI: 89.2 to 98.4) preembalming and postembalming, respectively. Preembalming and postembalming positive predictive value was 89.3% (95% CI: 71.8 to 97.7) and 83.3% (95% CI: 65.3 to 94.4), respectively. The area under the curve preembalming and postembalming was 94.9% (95% CI: 89.6 to 100) and 93.9% (95% CI: 88.5 to 99.4), respectively. CONCLUSIONS: The study showed a relatively high-performance sensitivity and specificity of OraQuick Rapid HIV-1/2 test among decedents, similar to those observed among living subjects. OraQuick Rapid HIV-1/2 presents a convenient and less invasive screening test for surveillance of HIV among decedents within a mortuary setting.

BACKGROUND: In resource-limited settings, underlying causes of death (UCOD) often are not ascertained systematically, leading to unreliable mortality statistics. We reviewed medical charts to establish UCOD for decedents at two high volume mortuaries in Kisumu County, Kenya, and compared ascertained UCOD to those notified to the civil registry. METHODS: Medical experts trained in COD certification examined medical charts and ascertained causes of death for 456 decedents admitted to the mortuaries from April 16 through July 12, 2019. Decedents with unknown HIV status or who had tested HIV-negative >90 days before the date of death were tested for HIV. We calculated annualized all-cause and cause-specific mortality rates grouped according to global burden of disease (GBD) categories and separately for deaths due to HIV/AIDS and expressed estimated deaths per 100,000 population. We compared notified to ascertained UCOD using Cohen's Kappa (κ) and assessed for the independence of proportions using Pearson's chi-squared test. FINDINGS: The four leading UCOD were HIV/AIDS (102/442 [23.1%]), hypertensive disease (41/442 [9.3%]), other cardiovascular diseases (23/442 [5.2%]), and cancer (20/442 [4.5%]). The all-cause mortality rate was 1,086/100,000 population. The highest cause-specific mortality was in GBD category II (noncommunicable diseases; 516/100,000), followed by GBD I (communicable, perinatal, maternal, and nutritional; 513/100,000), and III (injuries; 56/100,000). The HIV/AIDS mortality rate was 251/100,000 population. The proportion of deaths due to GBD II causes was higher among females (51.9%) than male decedents (42.1%; p = 0.039). Conversely, more men/boys (8.6%) than women/girls (2.1%) died of GBD III causes (p = 0.002). Most of the records with available recorded and ascertained UCOD (n = 236), 167 (70.8%) had incorrectly recorded UCOD, and agreement between notified and ascertained UCOD was poor (29.2%; κ = 0.26). CONCLUSIONS: Mortality from infectious diseases, especially HIV/AIDS, is high in Kisumu County, but there is a shift toward higher mortality from noncommunicable diseases, possibly reflecting an epidemiologic transition and improving HIV outcomes. The epidemiologic transition suggests the need for increased focus on controlling noncommunicable conditions despite the high communicable disease burden. The weak agreement between notified and ascertained UCOD could lead to substantial inaccuracies in mortality statistics, which wholly depend on death notifications.

BACKGROUND: Accurate data on HIV-related mortality are necessary to evaluate the impact of HIV interventions. In low- and middle-income countries (LMIC), mortality data obtained through civil registration are often of poor quality. Though not commonly conducted, mortuary surveillance is a potential complementary source of data on HIV-associated mortality. METHODS: During April-July 2019, we assessed HIV prevalence, the attributable fraction among the exposed, and the population attributable fraction among decedents received by two high-volume mortuaries in Kisumu County, Kenya, where HIV prevalence in the adult population was estimated at 18% in 2019 with high ART coverage (76%). Stillbirths were excluded. The two mortuaries receive 70% of deaths notified to the Kisumu East civil death registry; this registry captures 45% of deaths notified in Kisumu County. We conducted hospital chart reviews to determine the HIV status of decedents. Decedents without documented HIV status, including those dead on arrival, were tested using HIV antibody tests or polymerase chain reaction (PCR) consistent with national HIV testing guidelines. Decedents aged less than 15 years were defined as children. We estimated annual county deaths by applying weights that incorporated the study period, coverage of deaths, and mortality rates observed in the study. RESULTS: The two mortuaries received a total of 1,004 decedents during the study period, of which 95.1% (955/1004) were available for study; 89.1% (851/955) of available decedents were enrolled of whom 99.4% (846/851) had their HIV status available from medical records and post-mortem testing. The overall population-based, age- and sex-adjusted mortality rate was 12.4 per 1,000 population. The unadjusted HIV prevalence among decedents was 28.5% (95% confidence interval (CI): 25.5-31.6). The age- and sex-adjusted mortality rate in the HIV-infected population (40.7/1000 population) was four times higher than in the HIV-uninfected population (10.2/1000 population). Overall, the attributable fraction among the HIV-exposed was 0.71 (95% CI: 0.66-0.76) while the HIV population attributable fraction was 0.17 (95% CI: 0.14-0.20). In children the attributable fraction among the exposed and population attributable fraction were 0.92 (95% CI: 0.89-0.94) and 0.11 (95% CI: 0.08-0.15), respectively. CONCLUSIONS: Over one quarter (28.5%) of decedents received by high-volume mortuaries in western Kenya were HIV-positive; overall, HIV was considered the cause of death in 17% of the population (19% of adults and 11% of children). Despite substantial scale-up of HIV services, HIV disease remains a leading cause of death in western Kenya. Despite progress, increased efforts remain necessary to prevent and treat HIV infection and disease.

Understanding the characteristics of individuals who are newly diagnosed with HIV is critical to controlling the HIV epidemic. Characterizing this population can improve strategies to identify undiagnosed positives and assist in targeting the provision of HIV services to improve health outcomes. We describe the characteristics of newly diagnosed HIV cases in western Kenya from 124 health facilities. The study cohort cases were matched to prevent duplication and patients newly diagnosed between January and June 2015 were identified and descriptive analysis performed. Among 8664 newly identified HIV cases, during the pilot timeframe, 3.1% (n=265) had retested for HIV after initial diagnosis. Linkage to care was recorded for approximately half (45.3%, n = 3930) and 28.0% (n = 2425) had a CD4 count available during the pilot timeframe. The median baseline CD4 count was 332 cells/mL (IQR: 156-544). Among the newly diagnosed age 15 years or older with a CD4 test, 53.0% (n = 1216) were diagnosed late, including 32.9% (n = 755) who had advanced HIV at diagnosis. Factors associated with late diagnosis included being male and in an age group older than 34 years. In western Kenya, continued efforts are needed in the area of testing to enhance early HIV diagnosis and epidemic control.

BACKGROUND: Death is an important but often unmeasured endpoint in public health HIV surveillance. We sought to describe HIV among deaths using a novel mortuary-based approach in Nairobi, Kenya. METHODS: Cadavers aged 15 years and older at death at Kenyatta National Hospital (KNH) and City Mortuaries were screened consecutively from January 29 to March 3, 2015. Cause of death was abstracted from medical files and death notification forms. Cardiac blood was drawn and tested for HIV infection using the national HIV testing algorithm followed by viral load testing of HIV-positive samples. RESULTS: Of 807 eligible cadavers, 610 (75.6%) had an HIV test result available. Cadavers from KNH had significantly higher HIV positivity at 23.2% (95% CI: 19.3 to 27.7) compared with City Mortuary at 12.6% (95% CI: 8.8 to 17.8), P < 0.001. HIV prevalence was significantly higher among women than men at both City (33.3% vs. 9.2%, P = 0.008) and KNH Mortuary (28.8% vs. 19.0%, P = 0.025). Half (53.3%) of HIV-infected cadavers had no diagnosis before death, and an additional 22.2% were only diagnosed during hospitalization leading to death. Although not statistically significant, 61.9% of males had no previous diagnosis compared with 45.8% of females (P = 0.144). Half (52.3%) of 44 cadavers at KNH with HIV diagnosis before death were on treatment, and 1 in 5 (22.7%) with a previous diagnosis had achieved viral suppression. CONCLUSIONS: HIV prevalence was high among deaths in Nairobi, especially among women, and previous diagnosis among cadavers was low. Establishing routine mortuary surveillance can contribute to monitoring HIV-associated deaths among cadavers sent to mortuaries.

PROBLEM/CONDITION: Use of human immunodeficiency virus (HIV)-mortality surveillance data can help public health officials monitor, evaluate, and improve HIV treatment programs. Many high-income countries have high-coverage civil registration and vital statistics (CRVS) systems linked to case-based HIV surveillance on which to base HIV mortality estimates. However, in the absence of comprehensive CRVS systems in low- and medium-income countries, such as Kenya, mortuary surveillance can be used to understand the occurrence of HIV infection among cadavers. In 2015, a pilot HIV-related mortuary surveillance system was implemented in the two largest mortuaries in Nairobi, Kenya. CDC conducted an evaluation to assess performance attributes and identify strengths and weaknesses of the surveillance system pilot. PERIOD COVERED: Data collection: January 29-March 3, 2015; evaluation: November 2015. DESCRIPTION OF THE SYSTEM: The surveillance system objectives were to determine HIV positivity among cadavers at two mortuary sites in Nairobi, Kenya, and to determine annual cause-specific and HIV-specific mortality rates among the cadavers. Cadavers of persons aged >/=15 years at death admitted to either mortuary during a 33-day period were included. Demographic information and place and time of death were entered into a surveillance register. Cardiac blood was collected using transthoracic aspiration, and blood specimens were tested for HIV in a central laboratory. Causes of death were abstracted from mortuary and hospital records. Of the 807 cadavers brought to the mortuaries, 610 (75.6%) had an HIV test result available. The overall unadjusted HIV-positivity rate was 19.5% (119/610), which differed significantly by sex (14.6% among men versus 29.5% among women). EVALUATION: The evaluation was conducted using CDC guidelines for evaluating public health surveillance systems. The attributes of simplicity, flexibility, data quality (completeness and validity), acceptability, sensitivity, predictive value positive, representativeness, timeliness, and stability were examined. The evaluation steps included review of the surveillance system documents, in-depth interviews with 20 key informants (surveillance system staff, including mortuary and laboratory staff, and stakeholders involved in funding or implementation), and review of the surveillance database. RESULTS AND INTERPRETATION: Implementation of the pilot mortuary surveillance system was complex because of extensive paperwork and the need to collect and process specimens outside of business hours. However, the flexibility of the system accommodated multiple changes during implementation, including changes in specimen collection techniques and data collection tools. Acceptability was initially low among the mortuary staff but increased after concerns regarding workload were resolved. Timeliness of specimen collection could not be measured because time of death was rarely documented. Completeness of data available from the system was generally high except for cause of death (46.5%). Although the two largest mortuaries in Nairobi were included, the surveillance system might not be representative of the Nairobi population. One of the mortuaries was affiliated with the national referral hospital and included cadavers of admitted patients, some deaths might have occurred outside Nairobi, and data were collected for only 1 month. PUBLIC HEALTH ACTIONS: Mortuary surveillance can provide data on HIV positivity among cadavers and HIV-related mortality, which are not available from other sources in most sub-Saharan African countries. Availability of these mortality data will help describe a country's progress toward achieving epidemic control and achieving Joint United Nations Programme on HIV/AIDS 95-95-95 targets. To understand HIV mortality in high-prevalence regions, the mortuary surveillance system is being replicated in Western Kenya. Although a low-cost system, its sustainability depends on external funding because mortuary surveillance is not yet incorporated into the national AIDS strategic framework in Kenya.

BACKGROUND: A universal health care identifier (UHID) facilitates the development of longitudinal medical records in health care settings where follow up and tracking of persons across health care sectors are needed. HIV case-based surveillance (CBS) entails longitudinal follow up of HIV cases from diagnosis, linkage to care and treatment, and is recommended for second generation HIV surveillance. In the absence of a UHID, records matching, linking, and deduplication may be done using score-based persons matching algorithms. We present a stepwise process of score-based persons matching algorithms based on demographic data to improve HIV CBS and other longitudinal data systems. OBJECTIVE: The aim of this study is to compare deterministic and score-based persons matching algorithms in records linkage and matching using demographic data in settings without a UHID. METHODS: We used HIV CBS pilot data from 124 facilities in 2 high HIV-burden counties (Siaya and Kisumu) in western Kenya. For efficient processing, data were grouped into 3 scenarios within (1) HIV testing services (HTS), (2) HTS-care, and (3) within care. In deterministic matching, we directly compared identifiers and pseudo-identifiers from medical records to determine matches. We used R stringdist package for Jaro, Jaro-Winkler score-based matching and Levenshtein, and Damerau-Levenshtein string edit distance calculation methods. For the Jaro-Winkler method, we used a penalty (р)=0.1 and applied 4 weights (ω) to Levenshtein and Damerau-Levenshtein: deletion ω=0.8, insertion ω=0.8, substitutions ω=1, and transposition ω=0.5. RESULTS: We abstracted 12,157 cases of which 4073/12,157 (33.5%) were from HTS, 1091/12,157 (9.0%) from HTS-care, and 6993/12,157 (57.5%) within care. Using the deterministic process 435/12,157 (3.6%) duplicate records were identified, yielding 96.4% (11,722/12,157) unique cases. Overall, of the score-based methods, Jaro-Winkler yielded the most duplicate records (686/12,157, 5.6%) while Jaro yielded the least duplicates (546/12,157, 4.5%), and Levenshtein and Damerau-Levenshtein yielded 4.6% (563/12,157) duplicates. Specifically, duplicate records yielded by method were: (1) Jaro 5.7% (234/4073) within HTS, 0.4% (4/1091) in HTS-care, and 4.4% (308/6993) within care, (2) Jaro-Winkler 7.4% (302/4073) within HTS, 0.5% (6/1091) in HTS-care, and 5.4% (378/6993) within care, (3) Levenshtein 6.4% (262/4073) within HTS, 0.4% (4/1091) in HTS-care, and 4.2% (297/6993) within care, and (4) Damerau-Levenshtein 6.4% (262/4073) within HTS, 0.4% (4/1091) in HTS-care, and 4.2% (297/6993) within care. CONCLUSIONS: Without deduplication, over reporting occurs across the care and treatment cascade. Jaro-Winkler score-based matching performed the best in identifying matches. A pragmatic estimate of duplicates in health care settings can provide a corrective factor for modeled estimates, for targeting and program planning. We propose that even without a UHID, standard national deduplication and persons-matching algorithm that utilizes demographic data would improve accuracy in monitoring HIV care clinical cascades.

BACKGROUND: Cross-sectional population-based surveys are essential surveillance tools for tracking changes in HIV epidemics. In 2007, Kenya implemented the first AIDS Indicator Survey [Kenya AIDS Indicator Survey (KAIS) 2007], a nationally representative, population-based survey that collected demographic and behavioral data and blood specimens from individuals aged 15-64 years. Kenya's second AIDS Indicator Survey (KAIS 2012) was conducted to monitor changes in the epidemic, evaluate HIV prevention, care, and treatment initiatives, and plan for an efficient and effective response to the HIV epidemic. METHODS: KAIS 2012 was a cross-sectional 2-stage cluster sampling design, household-based HIV serologic survey that collected information on households as well as demographic and behavioral data from Kenyans aged 18 months to 64 years. Participants also provided blood samples for HIV serology and other related tests at the National HIV Reference Laboratory. RESULTS: Among 9300 households sampled, 9189 (98.8%) were eligible for the survey. Of the eligible households, 8035 (87.4%) completed household-level questionnaires. Of 16,383 eligible individuals aged 15-64 years and emancipated minors aged less than 15 years in these households, 13,720 (83.7%) completed interviews; 11,626 (84.7%) of the interviewees provided a blood specimen. Of 6302 eligible children aged 18 months to 14 years, 4340 (68.9%) provided a blood specimen. Of the 2094 eligible children aged 10-14 years, 1661 (79.3%) completed interviews. CONCLUSIONS: KAIS 2012 provided representative data to inform a strategic response to the HIV epidemic in the country.

BACKGROUND: HIV testing and counseling (HTC) is essential for successful HIV prevention and treatment programs. The national target for HTC is 80% of the adult population in Kenya. Population-based data to measure progress towards this HTC target are needed to assess the country's changing needs for HIV prevention and treatment. METHODS: In 2012-2013, we conducted a national HIV survey among Kenyans aged 18 months to 64 years. Respondents aged 15-64 years were administered a questionnaire that collected information on demographics, HIV testing behavior, and self-reported HIV status. Blood samples were collected for HIV testing in a central laboratory. Participants were offered home-based testing and counseling to learn their HIV status in the home and point-of-care CD4 testing if they tested HIV-positive. RESULTS: Of 13,720 adults who were interviewed, 71.6% [95% confidence interval (CI): 70.2 to 73.1] had been tested for HIV. Among those, 56.1% (95% CI: 52.8 to 59.4) had been tested in the past year, 69.4% (95% CI: 68.0 to 70.8) had been tested more than once, and 37.2% (95% CI: 35.7 to 38.8) had been tested with a partner. Fifty-three percent (95% CI: 47.6 to 58.7) of HIV-infected persons were unaware of their infection. Overall 9874 (72.0%) of participants accepted home-based HIV testing and counseling; 4.1% (95% CI: 3.3 to 4.9) tested HIV-positive, and of those, 42.5% (95% CI 31.4 to 53.6) were in need of immediate treatment for their HIV infection but not receiving it. CONCLUSIONS: HIV testing rates have nearly reached the national target for HTC in Kenya. However, knowledge of HIV status among HIV-infected persons remains low. HTC needs to be expanded to reach more men and couples, and strategies are needed to increase repeat testing for persons at risk for HIV infection.

BACKGROUND: Enhanced HIV surveillance using demographic, behavioral, and biologic data from national surveys can provide information to evaluate and respond to HIV epidemics efficiently. METHODS: From October 2012 to February 2013, we conducted a two-stage cluster sampling survey of persons aged 18 months to 64 years in 9 geographic regions in Kenya. Participants answered questionnaires and provided blood for HIV testing. We estimate HIV prevalence, HIV incidence, describe trends in HIV prevalence over the past five years, and identify factors associated with HIV infection. This analysis is restricted to persons aged 15 to 64 years. RESULTS: HIV prevalence was 5.6% (95% CI 4.9-6.3%) in 2012, a significant decrease from 2007, when HIV prevalence, excluding the North Eastern region, was 7.2% (95% CI 6.6-7.9%). HIV incidence was 0.4% (95% CI 0.2-0.6) in 2012. Among women, factors associated with undiagnosed HIV infection included being aged 35-39 years, divorced or separated, being from urban residences and Nyanza region, self-perceiving a moderate risk of HIV infection, condom use with the last partner, and reporting four or more lifetime number of partners. Among men, widowhood, condom use with the last partner, and lack of circumcision were associated with undiagnosed HIV infection. CONCLUSION: HIV prevalence has declined in Kenya since 2007. With improved access to treatment, HIV prevalence has become more challenging to interpret without data on new infections or mortality. Correlates of undiagnosed HIV infection provide important information on where to prioritize prevention interventions to reduce transmission of HIV in the broader population.

The President's Emergency Plan for AIDS Relief (PEPFAR) programme for the Caribbean Region was established in 2008 to address health system challenges, including fragile laboratory services and systems. The laboratory component of this programme consisted of several phases: assessment of laboratory needs of all 12 countries engaged in the programme; addressing gaps identified during the assessment; and monitoring and evaluation of the progress achieved. After one year of PEPFAR collaboration with national governments and other partners, laboratory services and systems greatly improved. Some of the milestones include: (1) the accreditation of a public laboratory; (2) improved access to HIV diagnosis with faster turnaround time; (3) establishment of capacity for platforms for DNA PCR, viral load and HIV drug resistance; (4) development of the laboratory workforce; and (5) establishment of a framework for implementation of sustainable quality management systems for laboratory accreditation. The progress recorded in strengthening laboratory health systems after one year of initiating this collaboration shows that with a rigorous initial assessment, programme design and intervention and strategic partnership, national laboratory health systems can be greatly enhanced to support programme implementation. Continued collaboration and country leadership is critical to create an integrated and sustainable laboratory network in the Caribbean.