Third party monitoring for health in Afghanistan: the good, the bad and the ugly.

Third party monitoring (TPM) is used in development programming to assess deliverables in a contract relationship between purchasers (donors or government) and providers (non-governmental organisations or non-state entities). In this paper, we draw from our experience as public health professionals involved in implementing and monitoring the Basic Package of Health Services (BPHS) and the Essential Package of Hospital Services (EPHS) as part of the SEHAT and Sehatmandi programs in Afghanistan between 2013 and 2021. We analyse our own TPM experience through the lens of the three parties involved: the Ministry of Public Health; the service providers implementing the BPHS/EPHS; and the TPM agency responsible for monitoring the implementation. Despite the highly challenging and fragile context, our findings suggest that the consistent investments and strategic vision of donor programmes in Afghanistan over the past decades have led to a functioning and robust system to monitor the BPHS/EPHS implementation in Afghanistan. To maximise the efficiency, effectiveness and impact of this system, it is important to promote local ownership and use of the data, to balance the need for comprehensive information with the risk of jamming processes, and to address political economy dynamics in pay-for-performance schemes. Our findings are likely to be emblematic of TPM issues in other sectors and other fragile and conflicted affected settings and offer a range of lessons learnt to inform the implementation of TPM schemes.

Finagle's laws of information: lessons learnt evaluating a complex health intervention in Nigeria.

Evaluations cannot support evidence-informed decision making if they do not provide the information needed by decision-makers. In this article, we reflect on our own difficulties evaluating the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) approach, an intervention that provides high-resolution demographic and geographical information to support health service delivery. GRID3 was implemented in Nigeria's northern states to support polio (2012-2019) and measles immunisation campaigns (2017-2018). Generalising from our experience we argue that Finagle's four laws of information capture a particular set of challenges when evaluating complex interventions: the weak causal claims derived from quasi-experimental studies and secondary analyses of existing data (the information we have is not the data we want); the limited external validity of counterfactual impact evaluations (the information we want is not the information we need); the absence of reliable monitoring data on implementation processes (the information we need is not what we can obtain) and the overly broad scope of evaluations attempting to generate both proof of concept and evidence for upscaling (the information we can obtain costs more than we want to pay). Evaluating complex interventions requires a careful selection of methods, thorough analyses and balanced judgements. Funders, evaluators and implementers share a joint responsibility for their success.

WASH, nutrition and health-seeking behavior during COVID-19 lockdowns: Evidence from rural Bangladesh.

A general lockdown to minimize to slow transmission of COVID-19 in Bangladesh came into effect on March 26th and lasted until May 30th. The lockdown had far-reaching economic implications for the population, with many facing economic hardship due to loss of income. Despite the attempt of the government to ease economic hardship by means of social safety net packages, people suffered from poor access to health services, and financial and food insecurity. This is likely to have disastrous consequences for the nutritional status of young children. This cross-sectional study measured the impact of the first general lockdown on food consumption of young children, access to water, handwashing and health seeking behavior, and the ability to maintain livelihood among households with children under the age of 5, in rural Bangladesh. The result of the analysis suggest that loss of income was reported by almost all respondents across all socio-economic groups. However, the poorest households were less likely to provide for sufficient food for their families and had to reduce consumption of food. Diet diversity and food intake-particularly animal protein sources-for young children were severely affected. On the other, increased awareness of handwashing and access to soap were also reported. The pandemic is likely to be detrimental to the nutritional status of children in Bangladesh and can exacerbate existing health inequities. Strong social safety net programs are needed to protect vulnerable populations to consequences of restrictive measures, supported in design and implementation by non-governmental organizations.

Assessment of tuberculosis case notification rate: spatial mapping of hotspot, coverage and diagnostics in Katsina State, north-western Nigeria.

Tuberculosis (TB) is prevalent in Nigeria, and Katsina, along with other 12 states in the country, accounts for a high proportion of unnotified TB cases: constituting the high priority-intervention States in the country. Interventions focused on TB detection and coverage in the state could benefit from a better understanding of hotspot Local Government Areas (LGAs) that trigger and sustain the disease. Therefore, this study investigated the spatial distribution of TB Case Notification Rates (CNRs), diagnostics and coverage across the LGAs. Using 2017 to 2019 TB case finding data, the geocoordinates of diagnostic facilities and shapefiles, a retrospective ecological study was conducted. The data were analysed with QGIS and GeoDa. Moran's I and LISA were used to locate and quantify hotspots. The coverage of microscopy and GeneXpert facilities was assessed on QGIS using a 5 km and 20 km radius, respectively. The CNR in the state, and 29 of the 34 LGAs, increased steadily from 2017 to 2019. Hotspots of high CNRs were also identified in 2017 (Moran's I=0.106, p-value=0.090) and 2018 (Moran's I=-0.020, p-value=0.370). While CNRs increased along with presumptive TB rates across most LGAs over the years, the positivity yield and bacteriological and Xpert diagnostic rates decreased. Bacteriological and GeneXpert coverage were 78% and 49% respectively. Additionally, only 51% of the state's population lived within 20km of a GeneXpert facility. These results suggest that TB program interventions had some positive impact on the CNR, however, diagnostic facilities need to be equitably distributed and more innovative approaches need to be explored to find the missing cases.

Finding gaps in TB notifications: spatial analysis of geographical patterns of TB notifications, associations with TB program efforts and social determinants of TB risk in Bangladesh, Nepal and Pakistan.

BACKGROUND: In order to effectively combat Tuberculosis, resources to diagnose and treat TB should be allocated effectively to the areas and population that need them. Although a wealth of subnational data on TB is routinely collected to support local planning, it is often underutilized. Therefore, this study uses spatial analytical techniques and profiling to understand and identify factors underlying spatial variation in TB case notification rates (CNR) in Bangladesh, Nepal and Pakistan for better TB program planning. METHODS: Spatial analytical techniques and profiling was used to identify subnational patterns of TB CNRs at the district level in Bangladesh (N = 64, 2015), Nepal (N = 75, 2014) and Pakistan (N = 142, 2015). A multivariable linear regression analysis was performed to assess the association between subnational CNR and demographic and health indicators associated with TB burden and indicators of TB programme efforts. To correct for spatial dependencies of the observations, the residuals of the multivariable models were tested for unexplained spatial autocorrelation. Spatial autocorrelation among the residuals was adjusted for by fitting a simultaneous autoregressive model (SAR). RESULTS: Spatial clustering of TB CNRs was observed in all three countries. In Bangladesh, TB CNR were found significantly associated with testing rate (0.06%, p < 0.001), test positivity rate (14.44%, p < 0.001), proportion of bacteriologically confirmed cases (- 1.33%, p < 0.001) and population density (4.5*10-3%, p < 0.01). In Nepal, TB CNR were associated with population sex ratio (1.54%, p < 0.01), facility density (- 0.19%, p < 0.05) and treatment success rate (- 3.68%, p < 0.001). Finally, TB CNR in Pakistan were found significantly associated with testing rate (0.08%, p < 0.001), positivity rate (4.29, p < 0.001), proportion of bacteriologically confirmed cases (- 1.45, p < 0.001), vaccination coverage (1.17%, p < 0.001) and facility density (20.41%, p < 0.001). CONCLUSION: Subnational TB CNRs are more likely reflective of TB programme efforts and access to healthcare than TB burden. TB CNRs are better used for monitoring and evaluation of TB control efforts than the TB epidemic. Using spatial analytical techniques and profiling can help identify areas where TB is underreported. Applying these techniques routinely in the surveillance facilitates the use of TB CNRs in program planning.