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Abstract Background Malaria is a significant public health burden, particularly in sub-Saharan Africa. Despite global efforts to reduce malaria incidence, various challenges, including socio-economic disparities, insecticide resistance, and climatic factors, continue to hamper malaria elimination in Ghana. Over the years, several interventions have been implemented to combat malaria. However, the implementation of these malaria interventions and their association with the malaria burden remains unclear. Aim This study evaluated the epidemiological behaviour of malaria in Tarkwa-Nsuaem Municipality from 2013 to 2023. Materials and methods Malaria incidence, severe cases, and mortality among children under five from 2013 to 2023 were obtained from the Tarkwa-Nsuaem Health Directorate. Meteorological data were sourced from the Global Climate Monitor, while intervention coverage data were extracted from the Malaria Atlas Project. The study employed the Mann-Kendall test to assess trends and applied Joinpoint regression to detect significant shifts in malaria incidence, severe cases, and mortality. Additionally, data on insecticide-treated net coverage and case management treatment were analyzed to evaluate intervention effectiveness. To further assess the influence of climate factors on malaria incidence, a Seasonal AutoRegressive Integrated Moving Average with Exogenous Variables model was applied. The best-fitting model, SARIMAX(1,1,1)x(1,1,1,12), incorporated rainfall and temperature as exogenous predictors to capture the temporal dynamics and seasonal variations in malaria incidence. Results Over the study period, 110,737 malaria cases were reported, with an annual mean incidence rate of 242.37 cases per 1,000 population. Malaria incidence increased significantly by 12.48% from 109.63 cases per 1,000 in 2013 to 234.41 in 2023 (p = 0.02). ITN coverage fluctuated between 27.21% and 51.82%, and treatment coverage improved steadily to 62.08%. Malaria-related deaths decreased significantly, with zero deaths reported since 2020. However, severe malaria cases showed a fluctuating trend, decreasing by 80.6% from 2013 to 2018, followed by a 110.3% increase from 2018 to 2023. The AutoRegressive Integrated Moving Average with Exogenous Variables model results indicated that rainfall was a significant predictor of malaria incidence (p = 0.032), while temperature did not show a statistically significant impact (p = 0.927). The model successfully captured historical trends and seasonal variations. Conclusions The study showed a significant reduction in malaria-related mortality in Tarkwa-Nsuaem, likely attributable to improved case management and treatment coverage. However, the fluctuating ITN coverage and the recent rise in severe cases warrant further investigation. Targeted interventions, especially in mining areas, and more consistent vector control measures are needed to sustain progress and further reduce malaria incidence.

This study examines cesarean section (C‐section) deliveries in Ghana from 2008 to 2017 in 10 regions, distinguishing between scheduled and emergency procedures. Scheduled C‐sections target specific maternal conditions, such as advanced age, multiparity, and medical history, while emergency C‐sections address acute fetal distress, preeclampsia, bleeding, and other urgent situations. The analysis reveals various regional patterns, with the Brong‐Ahafo Region showing a potential deceleration after 2017 and the Upper West Region indicating a possible acceleration. The high number of C‐sections in Greater Accra and Ashanti may be related to population density and health facilities. The study proposes empirical models, including linear, quadratic, and exponential components, emphasizing quasilinearity. The exponential model suggests transient and permanent phases of cesarean frequency, with the latter dominated by quasilinearity. Optimal parameter values are determined, which highlights the stability of the model. However, caution is advised when projecting too far into the future due to the inevitable slowing of observed trends. The findings offer insights for healthcare planning, resource allocation, and policymaking, emphasizing the need for region‐specific approaches and ongoing monitoring of cesarean dynamics to inform nuanced interventions. [ABSTRACT FROM AUTHOR]

In this study, a three-parameter modification of the Burr XII distribution has been developed through the integration of the weighted version of the alpha power transformation family of distributions. This newly introduced model, termed the modified alpha power-transformed Burr XII distribution, exhibits the unique ability to effectively model decreasing, right-skewed, or unimodal densities. The paper systematically elucidates various statistical properties of the proposed distribution. The estimation of parameters was obtained using maximum likelihood estimation. The estimator has been evaluated for consistency through simulation studies. To gauge the practical applicability of the proposed distribution, two distinct datasets have been employed. Comparative analyses involving six alternative distributions unequivocally demonstrate that the modified alpha power-transformed Burr XII distribution provides a better fit. Additionally, a noteworthy extension is introduced in the form of a location-scale regression model known as the log-modified alpha power-transformed Burr XII model. This model is subsequently applied to a dataset related to stock market liquidity. The findings underscore the enhanced fitting capabilities of the proposed model in comparison to existing distributions, providing valuable insights for applications in financial modelling and analysis. [ABSTRACT FROM AUTHOR]