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Background: The emergence of Plasmodium falciparum drug resistance against artemisinin-based combination therapy has threatened malaria control efforts. Since malaria control and elimination plans are dependent on these drugs, they must remain efficacious. However, resistance to these drugs was detected in low-transmission settings and is predicted to emerge in high-transmission settings, including in unspecified areas of Ethiopia. Therefore, this study aimed to assess the therapeutic efficacy and safety of artemether-lumefantrine for the treatment of uncomplicated P. falciparum malaria., Methods: A single-arm prospective observational study was conducted at Teda Health Centre, Northwest Ethiopia, by following the 2009 World Health Organization efficacy study guidelines from September 2022 to February 2023. Patients with uncomplicated falciparum malaria were conveniently selected and treated with a standard dose of artemether-lumefantrine, along with a single low dose of primaquine. Then clinical and parasitological responses and haemoglobin levels were assessed during the 28-day scheduled follow-up. Blood films were examined and asexual parasites were quantified; axillary temperature was measured; and drug adverse events were assessed throughout the follow-up. Finally, the drug efficacy (adequate clinical and parasitological response) was determined by Kaplan-Meier and per-protocol analyses. The data were analysed using the WHO Excel spreadsheet and SPSS version 25 software., Results: The success rates of PCR uncorrected and corrected Kaplan-Meier analysis on day 28 were 95.8% (95% CI 87.5-98.6) and 97.3% (95% CI 89.4-99.3), respectively. The per-protocol PCR uncorrected and corrected adequate clinical and parasitological responses were 95.5% (95% CI 87.5-99.1) and 97% (95% CI 89.5-99.6), respectively. On day-3, 97% of study participants were free of asexual parasitaemia, and all of them were fever-free on day-2. All of the gametocyte-positive patients at baseline were found to be negative for gametocytes on day-2. Moreover, the baseline mean hemoglobin of 13.10 g/dl increased slightly on day-14 to 13.27 g/dl but significantly on day-28 to 13.69 g/dl in a paired sample t test. All adverse events reported were mild., Conclusion: Artemether-lumefantrine continued to be an efficacious and safe drug for the treatment of uncomplicated Plasmodium falciparum malaria at the Teda Health Centre., Trial Registration: unique ID# PACTR202309773069812 at https://pactr.samrc.ac.za on September 1, 2023., (© 2024. The Author(s).)

Although the overall burden of malaria is decreasing in Ethiopia, a recent report of an unpredictable increased incidence may be related to the presence of community-wide gametocyte-carrier individuals and a high proportion of infected vectors. This study aimed to reveal the current prevalence of gametocyte-carriage and the sporozoite infectivity rate of Anopheles vectors for Plasmodium parasites. A community-based cross-sectional study was conducted from May 01 to June 30/2019. A total of 53 households were selected using systematic random sampling and a 242 study participants were recruited. Additionally,515 adult female Anopheles mosquitoes were collected using Center for Diseases Control and Prevention (CDC) light traps and mouth aspirators. Parasite gametocytemia was determined using giemsa stain microscopy, while sporozoite infection was determined by giemsa staining microscopy and enzyme linked immunosorbent assay (ELISA). Among the total 242 study participants, 5.4% (95%, CI = 2.9-8.3) of them were positive for any of the Plasmodium species gametocyte. Furthermore, being female [AOR = 15.5(95%, CI = 1.71-140.39)], age group between 15-29 years old [AOR = 16.914 (95%, CI = 1.781-160.63)], no ITNs utilization [AOR = 16.7(95%, CI = 1.902 -146.727)], and high asexual parasite density [(95%, CI = 0.057-0.176, P = 0.001, F = 18.402)] were identified as statistically significant factors for gametocyte carriage. Whereas sporozoite infection rate was 11.6% (95%, CI = 8.2-15.5) and 12.7% (95%, CI = 9.6-16.3) by microscopy and ELISA, respectively. Overall, this study indicated that malaria remains to be an important public health problem in Gondar Zuria district where high gametocyte carriage rate and sporozoite infection rate could sustain its transmission and burden. Therefore, in Ethiopia, where malaria elimination program is underway, frequent, and active community-based surveillance of gametocytemia and sporozoite infection rate is important., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Minwuyelet et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Malaria affects the intravascular environment, leading to abnormal coagulation activation, prolonged prothrombin time, and activated partial thromboplastin time. Despite the high prevalence of malaria in the study area, there has been little published research on the effects of Plasmodium infection on coagulation parameters., Objective: The aim was to assess the effect of malaria on basic coagulation parameters among patients attending Dembia Primary Hospital and Makisegnit Health Center., Methods: A cross-sectional study was carried out from January to March 2020. The study involved 120 participants. Blood specimens were collected, which were analyzed using a Huma Clot Due Plus analyzer. The collected data were entered into EpiData and exported to SPSS version 21 for analysis. Non-parametric statistical methods were employed to analyze the data. The results were considered statistically significant if the p-value was less than 0.05., Results: Individuals infected with Plasmodium exhibit coagulation disorders with elevated levels of PT (Prothrombin Time), APTT (Activated Partial Thromboplastin Time), and INR (International Normalization Ratio) in comparison to healthy controls. The median PT, APTT, and INR values for infected cases were measured at 20.5 [8.6], 39.5 [17.9], and 1.8 [0.9], respectively, while healthy controls had measurements of 15.1 [2.5], 28.8 [8.3], and 1.3 [0.2] (p ≤ 0.001). The severity of coagulation disorders increased with an increase in parasitemia levels. The type of Plasmodium species present had a significant impact on PT and INR values (p ≤ 0.001), whereas APTT did not show any significant impact across the Plasmodium species (p > 0.05)., Conclusion: The results of this study found that malaria has a substantial impact on various blood clotting parameters, including PT, APTT, and INR. Parasitemia severity is significantly associated with extended PT and INR, implying that the higher the parasitemia, the longer it takes for blood to clot. Furthermore, the study discovered that the PT and INR levels differed based on the type of Plasmodium species responsible for the infection., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Tesfaye et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: This study aims to develop and compare different models to predict the Length of Stay (LoS) and the Prolonged Length of Stay (PLoS) of inpatients admitted through the emergency department (ED) in general patient settings. This aim is not only to promote any specific model but rather to suggest a decision-supporting tool (i.e., a prediction framework)., Methods: We analyzed a dataset of patients admitted through the ED to the "Sant"Orsola Malpighi University Hospital of Bologna, Italy, between January 1 and October 26, 2022. PLoS was defined as any hospitalization with LoS longer than 6 days. We deployed six classification algorithms for predicting PLoS: Random Forest (RF), Support Vector Machines (SVM), Gradient Boosting (GB), AdaBoost, K-Nearest Neighbors (KNN), and logistic regression (LoR). We evaluated the performance of these models with the Brier score, the area under the ROC curve (AUC), accuracy, sensitivity (recall), specificity, precision, and F1-score. We further developed eight regression models for LoS prediction: Linear Regression (LR), including the penalized linear models Least Absolute Shrinkage and Selection Operator (LASSO), Ridge and Elastic-net regression, Support vector regression, RF regression, KNN, and eXtreme Gradient Boosting (XGBoost) regression. The model performances were measured by their mean square error, mean absolute error, and mean relative error. The dataset was randomly split into a training set (70%) and a validation set (30%)., Results: A total of 12,858 eligible patients were included in our study, of whom 60.88% had a PloS. The GB classifier best predicted PloS (accuracy 75%, AUC 75.4%, Brier score 0.181), followed by LoR classifier (accuracy 75%, AUC 75.2%, Brier score 0.182). These models also showed to be adequately calibrated. Ridge and XGBoost regressions best predicted LoS, with the smallest total prediction error. The overall prediction error is between 6 and 7 days, meaning there is a 6-7 day mean difference between actual and predicted LoS., Conclusion: Our results demonstrate the potential of machine learning-based methods to predict LoS and provide valuable insights into the risks behind prolonged hospitalizations. In addition to physicians' clinical expertise, the results of these models can be utilized as input to make informed decisions, such as predicting hospitalizations and enhancing the overall performance of a public healthcare system., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zeleke, Palumbo, Tubertini, Miglio and Chiari.)

This paper aimed to analyse the spatio-temporal patterns of the diffusion of SARS-CoV-2, the virus causing coronavirus 2019 (COVID-19, in the city of Bologna, the capital and largest city of the Emilia-Romagna Region in northern Italy. The study took place from February 1st, 2020 to November 20th, 2021 and accounted for space, sociodemographic characteristics and health conditions of the resident population. A second goal was to derive a model for the level of risk of being infected by SARS-CoV-2 and to identify and measure the place-specific factors associated with the disease and its determinants. Spatial heterogeneity was tested by comparing global Poisson regression (GPR) and local geographically weighted Poisson regression (GWPR) models. The key findings were that different city areas were impacted differently during the first three epidemic waves. The area-to-area influence was estimated to exert its effect over an area with 4.7 km radius. Spatio-temporal heterogeneity patterns were found to be independent of the sociodemographic and the clinical characteristics of the resident population. Significant single-individual risk factors for detected SARS-CoV-2 infection cases were old age, hypertension, diabetes and co-morbidities. More specifically, in the global model, the average SARS-CoV-2 infection rate decreased 0.93-fold in the 21-65 years age group compared to the >65 years age group, whereas hypertension, diabetes, and any other co-morbidities (present vs absent), increased 1.28-, 1.39- and 1.15-fold, respectively. The local GWPR model had a better fit better than GPR. Due to the global geographical distribution of the pandemic, local estimates are essential for mitigating or strengthening security measures.

Background: In Ethiopia, despite various public health intervention approaches have been implemented to eliminate malaria, its public health problem remains considerable. There are such numerous studies; however, investigating the trend of malaria infection in various settings is paramount for area-specific evidence-based interventions, evaluating ongoing malaria control programs. Hence, since the trend of malaria infection in Maksegnit has not yet been documented, this study is aimed at assessing the seven-year trend of malaria in Maksegnit Health Center., Methods: An institutional-based retrospective study was conducted to assess the trend of malaria prevalence over the last seven years (2014-2020) using recorded blood smear reports in the laboratory logbook in Maksegnit Health Center, Northwest Ethiopia., Result: Over the last seven years, a total of 28217 clinically malaria-suspected individuals were requested for blood film examination at Maksegnit Health Center. Of whom, microscopically confirmed malaria case was found in 4641/28217 (16.4%). A significant seasonal and interannual variation of malaria cases was observed ( P < 0.001). The highest prevalence was observed in years 2014 (25.5%) and 2020 (25.1%), while the minimum annual prevalence was seen in 2017/18 (6.4%). The month of October (25.5%) had the highest number of malaria cases documented, while February had the least (4.7%). Males and individuals under the age group of 15-45 were the most affected segments of the population. A significant interannual fluctuating prevalence of malaria cases was recorded ranging from 25.5% to 6.4% ( P < 0.001)., Conclusion: Malaria is still a public health threat in the study area despite significant fluctuating patterns of malaria was observed in the last seven years. In particular, a bounced back trend of malaria from 2018 to 2020 is alarming. Thus, the implementation of ongoing intervention approaches should be reconsidered, and uninterrupted efforts of the concerned bodies are still needed., Competing Interests: The authors declare that they have no competing interests., (Copyright © 2022 Tegegne Eshetu et al.)

This study aimed to identify and explore the hospital admission risk factors associated with the length of stay (LoS) by applying a relatively novel statistical method for count data using predictors among COVID-19 patients in Bologna, Italy. The second goal of this study was to model the LoS of COVID patients to understand which covariates significantly influenced it and identify the potential risk factors associated with LoS in Bolognese hospitals from 1 February 2020 to 10 May 2021. The clinical settings we focused on were the Intensive Care Unit (ICU) and ordinary hospitalization, including low-intensity stays. We used Poisson, negative binomial (NB), Hurdle-Poisson, and Hurdle-NB regression models to model the LoS. The fitted models were compared using the Akaike information criterion (AIC), Vuong's test criteria, and Rootograms. We also used quantile regression to model the effects of covariates on the quantile values of the response variable (LoS) using a Poisson distribution, and to explore a range of conditional quantile functions, thereby exposing various forms of conditional heterogeneity and controlling for unobserved individual characteristics. Based on the chosen performance criteria, Hurdle-NB provided the best fit. As an output from the model, we found significant changes in average LoS for each predictor. Compared with ordinary hospitalization and low-intensity stays, the ICU setting increased the average LoS by 1.84-fold. Being hospitalized in long-term hospitals was another contributing factor for LoS, increasing the average LoS by 1.58 compared with regular hospitals. When compared with the age group [50, 60) chosen as the reference, the average LoS decreased in the age groups [0, 10), [30, 40), and [40, 50), and increased in the oldest age group [80, 102). Compared with the second wave, which was chosen as the reference, the third wave did not significantly affect the average LoS, whereas it increased by 1.11-fold during the first wave and decreased by 0.77-fold during out-wave periods. The results of the quantile regression showed that covariates related to the ICU setting, hospitals with longer hospitalization, the first wave, and the out-waves were statistically significant for all the modeled quantiles. The results obtained from our study can help us to focus on the risk factors that lead to an increased LoS among COVID-19 patients and benchmark different models that can be adopted for these analyses.