Artificial dragonfly algorithm in the Hopfield neural network for optimal Exact Boolean k satisfiability representation.

This study proposes a novel hybrid computational approach that integrates the artificial dragonfly algorithm (ADA) with the Hopfield neural network (HNN) to achieve an optimal representation of the Exact Boolean kSatisfiability (EBkSAT) logical rule. The primary objective is to investigate the effectiveness and robustness of the ADA algorithm in expediting the training phase of the HNN to attain an optimized EBkSAT logic representation. To assess the performance of the proposed hybrid computational model, a specific Exact Boolean kSatisfiability problem is constructed, and simulated data sets are generated. The evaluation metrics employed include the global minimum ratio (GmR), root mean square error (RMSE), mean absolute percentage error (MAPE), and network computational time (CT) for EBkSAT representation. Comparative analyses are conducted between the results obtained from the proposed model and existing models in the literature. The findings demonstrate that the proposed hybrid model, ADA-HNN-EBkSAT, surpasses existing models in terms of accuracy and computational time. This suggests that the ADA algorithm exhibits effective compatibility with the HNN for achieving an optimal representation of the EBkSAT logical rule. These outcomes carry significant implications for addressing intricate optimization problems across diverse domains, including computer science, engineering, and business.

An assessment of primary health care costs and resource requirements in Kaduna and Kano, Nigeria.

Introduction: The availability of quality primary health care (PHC) services in Nigeria is limited. The PHC system faces significant challenges and the improvement and expansion of PHC services is constrained by low government spending on health, especially on PHC. Out-of-pocket (OOP) expenditures dominate health spending in Nigeria and the reliance on OOP payments leads to financial burdens on the poorest and most vulnerable populations. To address these challenges, the Nigerian government has implemented several legislative and policy reforms, including the National Health Insurance Authority (NHIA) Act enacted in 2022 to make health insurance mandatory for all Nigerian citizens and residents. Our study aimed to determine the costs of providing PHC services at public health facilities in Kaduna and Kano, Nigeria. We compared the actual PHC service delivery costs to the normative costs of delivering the Minimum Service Package (MSP) in the two states. Methods: We collected primary data from 50 health facilities (25 per state), including PHC facilities-health posts, health clinics, health centers-and general hospitals. Data on facility-level recurrent costs were collected retrospectively for 2019 to estimate economic costs from the provider's perspective. Statewide actual costs were estimated by extrapolating the PHC cost estimates at sampled health facilities, while normative costs were derived using standard treatment protocols (STPs) and the populations requiring PHC services in each state. Results: We found that average actual PHC costs per capita at PHC facilities-where most PHC services should be provided according to government guidelines-ranged from US$ 18.9 to US$ 28 in Kaduna and US$ 15.9 to US$ 20.4 in Kano, depending on the estimation methods used. When also considering the costs of PHC services provided at general hospitals-where approximately a third of PHC services are delivered in both states-the actual per capita costs of PHC services ranged from US$ 20 to US$ 30.6 in Kaduna and US$ 17.8 to US$ 22 in Kano. All estimates of actual PHC costs per capita were markedly lower than the normative per capita costs of delivering quality PHC services to all those who need them, projected at US$ 44.9 in Kaduna and US$ 49.5 in Kano. Discussion: Bridging this resource gap would require significant increases in expenditures on PHC in both states. These results can provide useful information for ongoing discussions on the implementation of the NHIA Act including the refinement of provider payment strategies to ensure that PHC providers are remunerated fairly and that they are incentivized to provide quality PHC services.

Determining staffing needs for improving primary health care service delivery in Kaduna State, Nigeria.

Background: The equitable distribution of a skilled health workforce is critical to health service delivery. Kaduna state has taken significant steps to revamp the primary health care system to ensure access to health care for its populace. However, these investments are yet to yield the desired outcomes due to health workforce shortages and the inequitable distribution of those available. Methods: A Workload Indicator for Staffing Need (WISN) study was conducted at Kaduna state's primary health care level. The study focused on estimating staffing requirements; Nurses/Midwives and Community Health Worker practitioners, Community Health Officers, Community Health Extension Workers, and Junior Community Health Extension Workers in all government-prioritised primary health care facilities. A total of ten focal primary health care facilities in Kaduna North Local Government Area (LGA) were included in the study. Results: Findings from the study revealed a shortage of Nurses/Midwives and Community Health Workers across the study facilities. For the Nurse/Midwife staffing category, nine of the ten PHCs have a WISN ratio < 1, indicating that the number of staff in the Nurse/Midwife category is insufficient to cope with the workload. In two of the ten primary health care facilities, there is an excess in the number of CHWs available; a WISN ratio > 1 was calculated. Conclusion: The WISN study highlights staffing needs in Kaduna State's government-prioritised primary health care facilities. This evidence establishes the basis for applying an evidence-based approach to determining staffing needs across the primary health care sector in the State to guide workforce planning strategies and future investments in the health sector. The World Health Organisation (WHO) WISN tool is useful for estimating staffing needs required to cope with workload pressures, particularly in a resource-constrained environment like Kaduna State.