Research Articles (Statistics)

Permanent URI for this collectionhttp://hdl.handle.net/2263/1835

A collection containing some of the full text peer-reviewed/ refereed articles published by researchers from
the Department of Statistics

Browse

Now showing 1 - 20 of 596

Knowledge and attitude of nurses in primary health care regarding climate change in Mpumalanga
Mabena, Marriot Mmama; Mooa, Ramadimetja Shirley; Masenge, Andries; Sepeng, Nombulelo Veronica (AOSIS, 2025-08-28)
BACKGROUND : Climate change is increasingly recognised as a critical public health challenge, a perspective reinforced by its inclusion as Sustainable Development Goal 13. Given its significant disease burden, climate change should be reframed as a leading health priority, demanding an immediate and coordinated response from the health sector. AIM : The aim of the study was to assess the knowledge and attitudes of professional nurses in primary health care regarding climate change. SETTING : The study was conducted in Nkangala District, Mpumalanga province. METHODS : A non-experimental, descriptive and quantitative research design, employing a self-administered questionnaire, was used to collect data. A comprehensive sampling of the entire population was conducted in the Thembisile Hani Local Municipality, Nkangala District, Mpumalanga, because of the small population size. RESULTS : About 82% of the professional nurses in primary health care had knowledge regarding the effects of climate change, and 23% did not link climate change to diseases. Regarding nurses’ attitudes and perceptions, approximately 66.2% strongly agreed that understanding the issue is crucial to providing effective patient care. In support, 29.8% agreed that it is essential to understand the issue to help patients, 3.3% were neutral, while 0.7% strongly disagreed and 0% disagreed. CONCLUSION : The findings of the study highlighted the importance of educating registered nurses about the mental health effects of climate change. It also emphasised the need to formally include climate change in the nursing curriculum, as many nurses currently depend on informal education to understand its implications. CONTRIBUTION : The results of the study will contribute new knowledge regarding climate change, its impact on health and its implications for the nursing profession. In addition, the study emphasised the importance of incorporating climate change into the nursing curriculum.
Determinants of the perceived financial threat of COVID-19 and implications for household economic stability : an application of the partial proportional odds model
Kassie, Maru Zewdu; Yilema, Seyifemickael Amare; Belay, Alebachew Taye; Rad, Najmeh Nakhaei; Chen, Ding-Geng (Din) (BioMed Central, 2025-08-22)
BACKGROUND : The COVID-19 pandemic has been one of the most significant global health crises in recent years. This study aimed to assess the determinants of perceived financial threat of COVID-19 and its implications on household’s economic stability in Ethiopia. METHODS : A cross-sectional study was conducted on 3058 households from the third round of the COVID-19 high-frequency phone survey of households (HFPS-HH) data, executed by the Central Statistical Agency of Ethiopia in partnership with the World Bank. The data were extracted and managed using STATA version 17. A partial proportional odds model was applied to assess the significant predictors that affect the perceived financial threat of COVID-19. RESULTS : The analysis revealed that 79.9% of respondents (95% CI: 78.5–81.4%) experienced some level of financial threat from the COVID-19 pandemic, with the majority of them (61.7%; 95% CI: 60.0–63.4%) perceiving it as a substantial financial threat. Key factors of financial threat included Age [AOR = 1.280, P = 0.008]; COVID-19 illness worry for substantial threat (AOR = 0.546, p < 0.001), for moderate threat (AOR = 0.562, P = 0.005)]; Ability to buy medicine for substantial threat [AOR = 0.546, p < 0.001], for moderate threat [AOR = 0.562, p = 0.005]; employed [AOR = 1.310, p = 0.014]; engagement in additional income activities for substantial threat [AOR = 3.428, p < 0.001], and for moderate threat [AOR = 3.043, P = 0.018]. CONCLUSION : The findings revealed that a significant proportion of respondents perceived COVID-19 as a financial threat, which adversely affected their economic stability. Vulnerability to financial threat was notably higher among older individuals, the unemployed, those unable to afford essential medicine, and respondents who expressed heightened concern about illness. In contrast, engagement in additional income-generating activities served as a protective factor. These results underscore the need for policymakers to prioritize inclusive social protection systems, expand access to affordable healthcare, promote employment opportunities, and facilitate income diversification. Such interventions are critical to enhancing household economic resilience and enabling a rapid response to future public health and economic crises. Additionally, future research should consider longitudinal designs to track changes in perceptions over time and incorporate broader economic indicators.
The incidence and role of EBV and HIV in head and neck lymphomas : an institutional study
Xoki, Buntu; Masenge, Andries; Kungoane, Tsholofelo (Elsevier, 2026-01)
OBJECTIVES : To determine the prevalence of Epstein-Barr virus (EBV) positive lymphomas in a cohort of patients with head and neck lymphomas and to correlate these lymphomas with HIV status, CD4+ cell count, clinical stage, and overall survival. STUDY DESIGN : This retrospective descriptive study sourced data from pathology reports and clinical records. Data collected included lymphoma type, HIV status, and medical information related to immunosuppression, CD4+ T-cell counts, HIV viral load, Ann Arbor clinical stage, and follow-up data. RESULTS : We reviewed 228 lymphomas, comprising 9 Hodgkin lymphomas and 219 non-Hodgkin lymphomas (HIV-positive: 133; HIV-negative: 23, and unknown HIV status: 72). Diffuse large B-cell lymphoma and plasmablastic lymphoma (PBL) were common and associated with HIV immune suppression, male sex, and middle age. Seventy-four lymphomas were Epstein-Barr encoded RNA in situ hybridization (EBER-ISH) positive. PBL was the most common EBV-driven lymphoma (median CD4+ count = 147 cells/mm3), with the highest Ann Arbor staging. CONCLUSION : These findings suggest that EBV infection is among the primary factors contributing to PBL oncogenesis in HIV-positive patients. Patients with PBL presented with CD4+ T-cell counts of <400 cells/mm3. Patients with HIV infection had a lower overall survival rate compared to HIV-negative patients, irrespective of lymphoma type. STATEMENT OF CLINICAL RELEVANCE : This study highlights the significant correlation between HIV infection and EBV-positive lymphomas in the head and neck regions, underscoring the need for vigilant screening and management strategies for lymphoma in HIV-positive patients to improve clinical outcomes.
Survival analysis of time-to-death for under-five children in Somalia : application of AFT modeling approach
Belay, Denekew Bitew; Chen, Ding-Geng (Din); Yismaw, Minilik Derseh; Mengste, Ashefet Agete; Yilema, Seyifemickael Amare; Ali, Mahad Ibrahim; Mohamed, Jama; Birhan, Nigussie Adam; Nigussie, Teshager Zerihun; Shiferaw, Yegnanew A.; Belay, Alebachew Taye; Fentaw, Kenaw Derebe (Elsevier, 2026-06)
OBJECTIVES : Sub-Saharan Africa continues to experience the highest under-five mortality rates globally, contributing 29.7% of all under-five deaths despite a 60% global decline between 1990 and 2022. This study aims to analyze time to death among children under five in Somalia and identify the key factors influencing child survival. STUDY DESIGN : The data used in this study is a population-based cross-sectional survey using a multistage stratified cluster sampling design. METHODS : In this study, 17,610 children under five from a Somalia 2020 demographic and health survey (DHS) were used. The accelerated failure time (AFT) model was used to analyze the time to death of under-five children. Survival time ratios (TR) and corresponding p-values were used to identify significant determinants of child survival. RESULTS : Of the total 17,610 children, about 689 children (3.91%) experienced the event (death). Several AFT models were compared, and the Weibull AFT model was selected as the best fit. The results of the Weibull AFT model showed that significant factors that influence child survival include maternal age at the first birth, preceding birth interval, the number of children ever born, and regional disparities. Longer birth intervals (18-59 months) increased survival time for the children, while shorter or excessively long intervals reduced survival. Mothers aged 20-29 at first birth showed a 49.2% increase in survival time (TR = 1.492; p = 0.003), compared to the younger mother. The shape parameter (0.607) suggests a declining hazard rate over time. CONCLUSIONS : This study highlights critical maternal, familial, and regional factors that influence child survival in Somalia. Strengthening targeted interventions, particularly those promoting optimal birth spacing and supporting younger mothers, may substantially improve under-five children survival outcomes.
Global, regional, and national prevalence and determinants of volunteer work : a meta-analysis study using survey data
Manda, S.O.M. (Samuel); Abdelatif, Nada; Seabe, Dineo; Millard, Sollie M.; Kamuruko, Tapiwa (Frontiers Media, 2025-07-07)
INTRODUCTION : While there is an increasing recognition of the role of volunteer work in promoting global development, the factors influencing volunteering at both global and regional levels remain poorly understood. This study employed a random-effects meta-analysis to estimate the prevalence of volunteering and to investigate variations in volunteer rates by gender, educational level, and age, both globally and at regional and country levels. METHODS : We analyzed data from 49,458 volunteers aged 15 and older across 37 World Values Surveys (WVS) conducted between 2000 and 2018 in 31 countries. Random-effects meta-analysis was employed to calculate the overall prevalence of volunteering and to compare volunteer rates among different demographic groups: females vs. males, individuals with at least a secondary education vs. those with primary education or less, and individuals aged 35 years or older versus those under 35 years. RESULTS : The overall pooled prevalence of volunteering was found to be 39.93% (95% CI: 33.25–46.62). Significant disparities in volunteering rates were observed across regions and countries, with the highest rates recorded in Africa (61.15%, CI: 50.54–77.77) and the lowest in Europe (28.97%, CI: 19.43–38.51). Rates varied considerably, from a low of 19.16% in Russia (CI: 19.16%–22.76%) to a high of 80.27% in Tanzania (CI: 77.99–82.55%) and 72.00% in Uganda (CI: 69.18–76.22%). Volunteering in religious organizations was the most common type, accounting for 16.77% (CI: 13.76–19.78), followed by community and health organizations at 14.62% (CI: 11.74–17.50). Regional differences were notable, with the highest rates of religious volunteering in Africa at 41.09% (CI: 20.17–62.02) and the lowest in Europe at 8.10% (CI: 5.25–10.95). The pooled relative risks for gender, educational, and age differentials were (RR = 0.91, 95% CI: 0.86–0.97); (1.20, CI: 1.18–1.36); and (1.00, CI: 0.95–1.05), respectively, indicating that only educational differentials significantly affected volunteering rates. The impact of education on volunteering was more pronounced in Europe (1.54, CI: 1.21–1.97) compared to Africa (1.17, CI: 1.03–1.33). CONCLUSIONS : Volunteering rates vary significantly by region and country, often correlating with individuals' educational levels. These findings are essential for policymakers aiming to enhance volunteer initiatives. By understanding the regional contexts and factors, such as the influence of education level on volunteering, policymakers can develop tailored programs that attract new volunteers and promote retention, ultimately fostering greater community engagement and social cohesion.
Spatial disparities of antenatal care utilization among pregnant women in sub-Saharan Africa— Bayesian geo-additive modelling approach
Belay, Denekew Bitew; Fenta, Haile Mekonnen; Birhan, Nigussie Adam; Chen, Ding-Geng (Din); Rad, Najmeh Nakhaei (Frontiers Media, 2025-06-27)
BACKGROUND : Antenatal care (ANC) is critical for ensuring healthy pregnancies and positive birth outcomes. Despite its importance, significant disparities in ANC access and utilization exist across sub-Saharan Africa (SSA), influenced by various socioeconomic, geographical, and systemic factors. This study aimed to analyze the spatial disparities in the proportion of recommended ANC utilization and its associated risk factors among pregnant women in 34 sub-Saharan African countries. METHOD : This study utilized the most recent Demographic and Health Survey (DHS) data from 34 countries across the SSA region. To assess the spatial disparities and their associated risk factors of ANC utilization, a geo-additive model via the Integrated Nested Laplace Approximation (INLA) was adopted. RESULT : The overall prevalence of recommended ANC utilization in SSA was 22.15%, with a significant difference between countries, ranging from 0.27% in Rwanda to 76.28% in Zimbabwe. Both Moran’s I and Geary’s C tests, with different neighborhood structures, evidenced the existence of spatial autocorrelation of ANC utilization among women in SSA countries. A Bayesian geo-additive model with Besag-York-Mollié (BYM) mixed effect was found to be the best model to assess the spatial dependencies and the non-linear effects of the factors on ANC utilization among women of reproductive age. The study showed that the existence of spatial disparities in ANC utilization and media exposure, as well as the mother’s work status, partner’s working status, age of mother, age at first cohabitation, and place of delivery, has a significant effect on ANC utilization. CONCLUSION : The overall coverage of recommended ANC in SSA countries falls short of the global minimum recommended ANC utilization. The lower coverage and inequality of ANC utilizations are influenced by underutilization of healthcare services, economic status, women’s education coverage, poor/absence of transportation facilities, and media exposure related to healthy reproduction. Empowering women through different media outlets, strengthening their economic power, easy access to health facilities, and decision-making power increases maternal healthcare service utilization.
Effects of vector control interventions on spatio-temporal changes of Falciparum malaria risk in children aged 2-10 in sub-Saharan African regions during 2011-2020
Chol, Changkuoth Jock; Belay, Denekew Bitew; Fenta, Haile Mekonnen; Chen, Ding-Geng (Din) (Frontiers Media, 2025-07-02)
BACKGROUND : Sub-Saharan Africa (SSA) has a disproportionately high malaria fatality rate globally, with young children accounting for the majority of fatalities. The objective of this study is to investigate the spatiotemporal dynamics of malaria infection risk and assess the effect of vector control interventions on malaria infection rates in SSA nations. METHODS : We utilized data from the Malaria Atlas Project regarding the prevalence of Plasmodium falciparum malaria infections and vector control interventions across 634 administrative areas in 45 SSA countries over a decade. This study adopted spatiotemporal regression models using Markov-chain Monte Carlo methods with a Bayesian setup. RESULTS : Between 2011 and 2020, the average annual prevalence rates of malaria infection among children aged 2 to 10 in SSA diminished from 21.32% in 2011 to 16.75% in 2016, with a slight resurgence observed in 2017. Each unit increase in the number of individuals utilizing insecticide-treated nets (ITN) annually correlates with a 34.07% reduction in the risk of malaria infection. A rise in malaria cases has prompted SSA to undertake serious control measures. The auto-regressive process reveals a highly significant temporal correlation, while the global spatial dependency parameter indicates a modest spatial correlation. The highest risk of malaria infection prevalence among children aged 2 to 10 was indicated in states in the West-central, Central, and certain Eastern regions. CONCLUSION : Given that the West-central, Central, and select Eastern states exhibit the highest rates of malaria infection, the global end malaria councils and the malaria control and elimination program should prioritize interventions in these regions, enhancing vector control measures and providing comprehensive training on their effective utilization to mitigate malaria risk in these areas.
Exploring machine learning classification for community based health insurance enrollment in Ethiopia
Yilema, Seyifemickael Amare; Shiferaw , Yegnanew A.; Moyehodie, Yikeber Abebaw; Fenta , Setegn Muche; Belay, Denekew Bitew; Fenta, Haile Mekonnen; Nigussie, Teshager Zerihun; Chen, Ding-Geng (Din) (Frontiers Media, 2025-07-18)
BACKGROUND : Community-based health insurance (CBHI) is a vital tool for achieving universal health coverage (UHC), a key global health priority outlined in the sustainable development goals (SDGs). Sub-Saharan Africa continues to face challenges in achieving UHC and protecting individuals from the financial burden of disease. As a result, CBHI has become popular in low- and middle-income countries, including Ethiopia. Therefore, this study aimed to identify the ML algorithm with the best predictive accuracy for CBHI enrollment and to determine the most influential predictors among the dataset. METHODS : The 2019 Ethiopian Mini Demographic and Health Survey (EMDHS) data were used. The CBHI were predicted using seven machine learning models: linear discriminant analysis (LDA), support vector machine with radial basis function (SVM), k-nearest neighbors (KNN), classification and regression tree (CART), and random forest (RF). Receiver operating characteristic curves and other metrics were used to evaluate each model’s accuracy. RESULTS : The RF algorithm was determined to be the best machine learning model based on different performance assessments. The result indicates that age, wealth index, household members, and land usage all significantly affect CBHI in Ethiopia. CONCLUSION : This study found that RF machine learning models could improve the ability to classify CBHI in Ethiopia with high accuracy. Age, wealth index, household members, and land utilization are some of the most significant variables associated with CBHI that were determined by feature importance. The results of the study can help health professionals and policymakers create focused strategies to improve CBHI enrollment in Ethiopia.
Knowledge, attitudes and practices regarding bovine tuberculosis in cattle and humans in Malawi
Ngwira, Alfred; Manda, S.O.M. (Samuel); Karimuribo, Esron Daniel; Kimera, Sharadhuli Iddi (Public Library of Science, 2026-02)
BACKGROUND : Bovine tuberculosis (BTB) has a significant impact on both the cattle industry and human health. Understanding its transmission, clinical signs, risk factors, and control measures is essential for prevention. This study aimed to evaluate the knowledge, attitudes, and practices regarding BTB in high-burden areas of Malawi. METHODS : A stratified sampling design was employed to collect data from 463 butchers, dairy farmers and cattle farmers in different locations and settings in Malawi. Aggregate scores on knowledge, attitudes, and practices were taken as multivariate measurements and fitted with multivariate linear regression models. RESULTS : Participants displayed satisfactory knowledge (88.68%), negative attitudes towards risky behaviours (92.27%), and appropriate practices (86.83%) concerning BTB. Most were aware of its presence in cattle (85.71%) and potential transmission to humans (74.09%), yet exhibited gaps in understanding clinical signs and held misconceptions about hereditary transmission. Many participants demonstrated risky behaviours, such as consuming raw animal products and selling products from infected animals. Individuals with secondary (β: −2.148; 95% CI: −4.168, −0.127) and tertiary education (β: −3.488; 95% CI: −6.626, −0.349) exhibited more negative attitudes towards risky behaviours compared to those with informal education. Adults aged 18−30 (β: −2.777; 95% CI: −5.469, −0.085) and those aged 31−45 (β: −3.035; 95% CI: −5.752, −0.319) demonstrated better protective practices than youths under 18. CONCLUSION : There is an urgent need for targeted health education on BTB, focusing on clinical signs and the myth of hereditary transmission, particularly aimed at young people, individuals with limited formal education, and farmers, to enhance prevention efforts.
A multivariate GARCH model with time-varying correlations : what do inflation data show in Ethiopia?
Likassa, Habte Tadesse; Chen, Ding-Geng (Din); Nadarajah, Saralees; Sema, Meskerem; Chen, Jenny K.; Temesgen, Shibru; Gotu, Butte (Springer, 2026)
Please read abstract in the article.
Pedal power : female cyclists at 94.7 Ride Joburg face fewer illnesses but more injuries and finishing challenges
Janse van Rensburg, Dina Christina; Swart, Xan; Ramagole, Dimakatso Althea; Du Toit, Francois Christiaan; Viljoen, Carel Thomas; Botha, Tanita; Phalane, Mahlane; Beeton, Ramona; Jansen van Rensburg, Audrey (Edizioni Minerva Medica, 2026-02)
BACKGROUND: Mass participation in amateur cycling events is popular, and ensuring participant safety is crucial. This study aimed to determine the epidemiology of medical encounters (MEs), including injury and illness, at mass-participation amateur cycling events and to explore associated risk factors. METHODS: We conducted a cross-sectional, descriptive, exploratory analysis of operational data collected during the 2015-2016 94.7 Ride Joburg cycling race. Outcomes include frequency (N., %), prevalence (%), incidence (injuries/1000 participants), did-not-finish (DNF, %), and Odds Ratio (OR, 95%CI). RESULTS: In total, 44849 individuals, mean age 40.06±11.68, participated in the 94.7 Ride Joburg cycling race during 2015-2016. We report the prevalence for MEs (5.3%) (injury: 1.7%, illness: 3.6%). The incidence of all MEs was 52.71 (50.61-54.88) (injury: 16.79 [15.61-18.03], illness: 35.92 [34.19-37.72]). Most race participants were male (79.0%), aged 31-50 (58.9%). Older age decreased the odds of injury, illness, or not finishing (P<0.001). Females had higher odds of injury (OR:1.43; 1.21-1.67; P<0.001) and for DNF (OR:1.57; 1.46-1.70; P<0.001) but lower odds of illness (OR:0.73; 0.64-0.64; P<0.001), compared to males. Overall, 7.9% of participants DNF, 6.9% had MEs, 3.2% were injured, and 3.8% were ill. Medical point location and distance were not significantly associated with medical encounters. CONCLUSIONS: Older participants have lower odds of injury and illness encounters. Females have higher odds of injury encounters and not finishing the race but lower odds of illness encounters than males. These findings offer insights into injury and illness at mass-participation amateur cycling events.
Type I multivariate Pólya-Aeppli distributions with applications
Geldenhuys, Claire; Ehlers, Rene; Bekker, Andriette, 1958- (Elsevier, 2026-03)
An extensive body of literature exists that specifically addresses the univariate case of zero-inflated count models. In contrast, research pertaining to multivariate models is notably less developed. We propose two new parsimonious multivariate models that can be used to model correlated multivariate overdispersed count data. Furthermore, for different parameter settings and sample sizes, various simulations are performed. In conclusion, we demonstrate the performance of the newly proposed multivariate candidates on two benchmark datasets, which surpasses that of several alternative approaches.
The modified Fréchet-exponentiated exponential distribution : novel model for reliability and survival analysis
Aga, Merga Abdissa; Dugasa, Shibiru Jabessa; Tadese, Habte; Chen, Ding-Geng (Din) (Wiley, 2026-01-21)
This study introduces a novel statistical model called the modified Fréchet-exponentiated exponential (MFrEE) distribution. The existing exponentiated exponential (EE) distribution, while useful for lifetime and reliability data, has limited flexibility in capturing diverse hazard shapes and may not adequately model extreme events or tail behavior. To address these limitations, the MFrEE distribution applies a modified Fréchet generator to the EE baseline, enhancing the model’s flexibility and robustness. Its survival and hazard functions, cumulative distribution function, and probability density function are derived, presented, and illustrated with plots for various parameter values. The study provides a comprehensive mathematical analysis of the distribution, deriving its moments, mean, variance, quantiles, and moment-generating function. Methodologically, the model is simulated using an accept–reject algorithm, and its parameters are estimated via maximum likelihood estimation (MLE). The performance of the estimators is assessed through Monte Carlo simulations using bias, mean squared error, and coverage probability (CP), with the CP results showing values close to the nominal 95% level across different parameter settings. Furthermore, the robustness and performance of the proposed method are evaluated using AIC, BIC, and AICc, demonstrating superior performance compared to baseline methods across three publicly available datasets. The study concludes by proposing this model as a significant contribution to probability theory and suggests two avenues for future research: applying the model to more real-world problems and using machine learning methods for parameter estimation to compare with the MLE approach used in this study.
Sushila-Poisson distribution : a flexible tool for survival and reliability modeling
Daghagh, Sepideh; Iranmanesh, Anis; Rad, Najmeh Nakhaei; Ormoz, Ehsan (OICC Press, 2025-03-31)
This paper presents a new type of Sushila distribution that provides greater flexibility for modelling lifetime data. This model, called the Sushila-Poisson (SP) distribution, is created by combining the Sushila and Poisson distributions. The three-parameter SP distribution represents various shapes of hazard rate functions, including upside-down bathtub, bathtub-shaped, increasing, and decreasing hazard rates, which are commonly encountered in fields such as medicine, engineering, economics, and the natural sciences. Therefore, the proposed model offers great potential for applications in these areas. The new model includes several known distributions, such as the Lindley, Lindley-Poisson, and Sushila distributions, as special cases. Several statistical properties of the SP distribution have been derived in this study. Simulation studies were conducted to examine the performance of the maximum likelihood estimators, which were developed using the Expectation-Maximization (EM) algorithm. The flexibility of the new model was further demonstrated through its application to three real data sets.
The effects of environmental and management factors on the quality of the corpus luteum and subsequent conception rates of beef and dairy cows in South Africa
Demont, Kaylee Jade; Webb, E.C. (Edward Cottington); Treadwell, Robert; Masenge, Andries (MDPI, 2025-10-30)
The corpus luteum (CL) controls the success of pregnancy. The current study investigated the effects of some environmental and management factors on the development of the CL and the subsequent impact on conception rates of beef and dairy cows in South Africa. Cows (Jersey, Holstein, Nguni, Bonsmara, Tuli, Ankole, Charolais and Angus crosses) receiving an embryo were synchronized based on the breed type and status. Standing estrus was observed from day 9 to day 12 after synchronization. Embryo transfer occurred on day 18. CLs were graded based on size and consistency of each CL by an experienced veterinarian. Production type (beef versus dairy types) was marginally associated with conception after the first synchronization cycle (p = 0.065). Cows were moved between groups, and this influenced the CL (p = 0.08). Climatological factors, maximum THI (p = 0.017) and precipitation (p = 0.061) influenced the quality of the CL in dairy cows. By contrast, precipitation (p = 0.067) influenced the quality of CLs in beef cows. More attention needs to be paid to the management of maximum THI and shelter from precipitation in dairy production systems, while precipitation alone was more important in beef cows. Climate affects the corpus luteum quality of cows of different production types differently.
A phenomenological methodology for wave detection in epidemics
Brettenny, Warren; Holloway, Jenny; Fabris-Rotelli, Inger Nicolette; Dudeni-Tlhone, Nontembeko; Abdelatif, Nada; Le Roux, Wouter; Manjoo-Docrat, Raeesa; Debba, Pravesh (Springer, 2026-03)
In both the management and modelling of epidemic outbreaks, the ability to determine the start of a wave of infections is of vital importance. Not only does this advantage the modelling of the outbreak, but, if done in real-time, can assist with a nation’s response to the disease. In this study, a bidirectional long-short-term-memory (Bi-LSTM) network is used to determine the start and end of the COVID-19 waves experienced in the district and metropolitan municipalities of Gauteng, South Africa, from 2020-2022 as well as the waves of the cholera outbreaks occurring in the Beira area of Mozambique between 1999 and 2005, in real-time. The problem of real-time scaling of the data prior to the first wave of an epidemic is addressed using globally available real-time information from first waves experienced in other countries and independent territories alongside the observed South African data. The use of the Bi-LSTM predicted starting dates is demonstrated for the second waves of COVID-19 infections experienced in Gauteng in 2020/21. Using the predicted starting dates, spatial-SEIR models are used to predict hospitalisations as a result of COVID-19 infections in each of the district and metropolitan municipalities of Gauteng. The fitted Bi-LSTM model demonstrates effectiveness in predicting the start and end dates of epidemic waves in real-time, allowing for pre-emptive disease modelling and predictions of spread. Moreover, it is shown that the use cases for the fitted model are not limited to COVID-19 studies, but can also be applied to other disease outbreaks that follow similar wave patterns.
Exploring on- and off-site waste management practices of informal dwellers in South Africa
Niyobuhungiro, Rissa; Schenck, Catherina; Fletcher, Lizelle; Von Fintel, Marisa (Taylor and Francis, 2025-07-04)
Household waste is a major contributor to environmental pollution and health issues. This article explores waste management practices at the household level in low-income informal housing areas in the Western Cape and Eastern Cape provinces of South Africa. The data collection consisted of a waste baseline assessment of household waste management and mapping and analysing illegal dumping spots in the immediate vicinity of the informal areas. Data were analysed using IBM SPSS Statistics 29. None of the municipalities in the study provides outside bins to households in informal areas. Approximately eighty-four percent (83.8%) of households in the study area receive some form of refuse removal, but illegal dumping was found in all areas. The results show that weekly collection of waste is not sufficient due to the limited space available to informal dwellers. Engagement with communities is important to collaboratively co-design locally appropriate ways of managing waste.
Illness is common in trail runners during training : a prospective cohort study
Janse van Rensburg, Dina Christina; Jansen van Rensburg; Audrey; Boer, Pieter Henk; Serero, Precious; Botha, Tanita; Schoeman, Marlene; Viljoen, Carel Thomas (Elsevier, 2026)
OBJECTIVES : Trail runners often experience illness during event preparation. We aimed to prospectively determine prevalence, incidence, clinical characteristics, severity (time-loss, burden) and associated illness risk factors amongst South African male and female recreational trail runners of different ages over a 30-week training period. DESIGN : Prospective cohort. METHODS : Illness and training data from 152 trail runners (120 males, 32 females) were collected every 14 days over 30 weeks using the updated OSTRC-H questionnaire. Illness prevalence (%), incidence (I: per 1000 trail running exposure-days), incidence ratio (IR), severity [% time-loss; illness burden (IB: days lost/1000 trail running exposure-days)], and associated risk factors are reported. RESULTS : Over 30 weeks, 52 % of runners reported illness, with a mean two-week all-illness prevalence of 10.1 %. The overall illness incidence was 7.2 (95 % CI: 5.7–9.2). The winter-to-summer IR was 1.6 (p = 0.022). Illness incidence in females (I = 9.7) was higher than in males (I = 6.6), with a female:male IR of 1.5 (p < 0.05). Most illnesses affected the respiratory (64.3 %), digestive (15.9 %) and musculoskeletal (5.7 %) systems. Moderate illness severity (8–28 days time-loss) occurred in 29.3 % of runners. The overall IB was 43.2 days lost. BMI ≥ 25 kg/m2 was associated with illness, but no significant illness risk factors were identified via Poisson regression. CONCLUSIONS : During a 30-week training period, 52 % of runners reported illness, with a higher incidence in females. The respiratory tract accounted for > 60 % of illnesses. One in three trail runners experienced > one week time-loss. A higher BMI > 25 kg/m2 was associated with illness. Further research is needed to identify risk factors and develop prevention strategies. PRACTICAL IMPLICATIONS • Prioritise respiratory health monitoring • Screen for high-risk profiles early • Tailor strategies for females and higher-BMI runners • Inform trail running guidelines HIGHLIGHTS • Trail runners show an illness prevalence of 10.1% during training. • Females experience significantly higher illness incidence than males. • Illness mainly affects the respiratory system of trail runners during training. • Approximately one-third of trail runners suffer from moderate to severe illness, resulting in > 8 days of time-loss in a 30-week training period. • Trail runners with a higher BMI (> 25 kg/m2) are more susceptible to illness.
Spatio-temporal variation of malaria incidence in Sub-Saharan Africa from 2011 to 2020
Chol, Changkuoth Jock; Belay, Denekew Bitew; Fenta, Haile Mekonnen; Chen, Ding-Geng (Din) (Taylor & Francis Group, 2025-04-14)
BACKGROUND : Malaria continues to pose a severe danger to health, social, and economic development in sub-Saharan Africa (SSA). Malaria in SSA requires a tremendous effort to eradicate. This study aimed to explore clusters of malaria incidence both spatially and temporally in the regions of the SSA countries using spatial autocorrelation statistics and univariate functional spatial scan statistics. METHODS : The study was done in 634 administrative areas throughout SSA nations. We used secondary data from the Malaria Atlas Project between 2011 and 2020. To convert malaria cases into incidence, the population at risk has been projected. To measure spatial autocorrelation, Global Moran’s 𝐼 was selected to examine feature positions and values. The Local Moran statistic was applied to identify regions dissimilar from their neighborhood. The Getis-Ord Local G* was employed to identify hot spots and cold spots areas in the SSA region. Furthermore, the univariate functional spatial scan statistic was used to see if spatial data tended to aggregate. RESULTS : The results revealed that the spatial and temporal clusters were statistically significant during the study period. Spatio-temporal scanning identified three high-risk malaria incidence areas in SSA. The regions around West-central, Central, and Southeast of SSA have a high-risk malaria incidence throughout the study period. CONCLUSIONS : The West-Central, Central, and Southeast regions of SSA had a high risk of malaria. Due to that, global end malaria councils should mobilize multi-sectional action, resources, advocacy, and accountability to support the national malaria program and national strategic plan to take and coordinate action across sectors to fight malaria.
Determinants of chronic malnutrition among under-five children in Ethiopia using simultaneous quantile regression
Warssamo, Birhanu Betela; Belay, Denekew Bitew; Chen, Ding-Geng (Din) (Nature Research, 2025-10-22)
Child malnutrition remains a challenge in Ethiopia despite progress in development goals. Stunting in children under five leads to disease, impaired development, and increased mortality. Earlier studies have used linear and logistic regressions to identify the drivers of stunting. These models overlook variations across outcome distributions. This study employed simultaneous quantile regression to identify the association between chronic malnutrition across different height-for-age z-score (HAZ) quantiles in children under the age of five. Data were drawn from the 2016 Ethiopian Demographic and Health Survey, including 8,592 women aged 15 – 49 years and their under-five children. After cleaning missing variables, HAZ score served as the dependent variable. Simultaneous quantile regression modeled covariates across multiple quantiles. The findings indicated that 34.75% of children were stunted. Significant variables associated with HAZ score included place of residence, shared toilet facility, respondent employed, vaccination, succeeding birth interval in months, frequency of checking antenatal care, literacy, type of toilet facility, anemia level, wealth index of household, twin status, place of delivery, highest level of education of mother and father and age of child. The association of these factors varied across quantiles, with slope differences between the 10th and 90th quantiles. The quantile regression plots for the selected quantiles 10th to 90th revealed significant differences in the association of the covariates across the HAZ quantiles under consideration. Quantile regression revealed that various factors work differently across the HAZ distribution. Findings demonstrate the benefit of quantile regression in revealing differential impacts and guiding targeted policy. Addressing stunting requires coordinated efforts to enhance child nutrition and achieve the Sustainable Development Goals by 2030.

Browse

Recent Submissions