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Abstract Background The cause of the high HIV prevalence in sub-Saharan Africa is incompletely understood, with heterosexual penile-vaginal transmission proposed as the main mechanism. Heterosexual HIV transmission has been estimated to have a very low probability; but effects of cofactors that vary in space and time may substantially alter this pattern. Methods To test the effect of individual variation in the HIV infectiousness generated by co-infection, we developed and analyzed a mathematical sexual network model that simulates the behavioral components of a population from Malawi, as well as the dynamics of HIV and the co-infection effect caused by other infectious diseases, including herpes simplex virus type-2, gonorrhea, syphilis and malaria. Results The analysis shows that without the amplification effect caused by co-infection, no epidemic is generated, and HIV prevalence decreases to extinction. But the model indicates that an epidemic can be generated by the amplification effect on HIV transmission caused by co-infection. Conclusion The simulated sexual network demonstrated that a single value for HIV infectivity fails to describe the dynamics of the epidemic. Regardless of the low probability of heterosexual transmission per sexual contact, the inclusion of individual variation generated by transient but repeated increases in HIV viral load associated with co-infections may provide a biological basis for the accelerated spread of HIV in sub-Saharan Africa. Moreover, our work raises the possibility that the natural history of HIV in sub-Saharan Africa cannot be fully understood if individual variation in infectiousness is neglected.

Background: Men who have sex with men (MSM) are disproportionately impacted by HIV in sub-Saharan Africa (SSA), where condomless anal intercourse (CAI) is a major driver of HIV transmission among this hidden subpopulation., Objectives: To determine CAI drivers and prevalence among HIV-positive and HIV-negative MSM., Method: Data from 1538 MSM who participated in a biobehavioural survey in Zimbabwe were used. Secondary statistical data analysis methods were used to determine prevalences and drivers of CAI., Results: A high prevalence of CAI, of at least 30%, among HIV-positive and HIV-negative MSM was found. Factors that led to a statistically significant higher CAI among HIV-positives compared to HIV-negatives included drunkenness (35% vs. 25%, P = 0.01), fear of partner (13% vs. 9%, P = 0.017), trusting the partner (10% vs. 6%, P = 0.008), and being offered more money (10% vs. 6%, P = 0.003)., Conclusion: Our findings indicate that economic, socio-behavioural and perceptual dimensions increase men's likelihood to engage in risky sexual behaviour, suggesting the need for HIV prevention efforts that provide tailored education regarding HIV risk among MSM in SSA. This is the first large biobehavioural survey that generated valuable information useful for analysing condomless anal sex among MSM in Zimbabwe., Competing Interests: The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article., (© 2024. The Authors.)

Caesarean sections (CSs) have increased globally, with concerns being raised involving overutilisation and inequalities in access. In Zimbabwe, where healthcare access varies greatly, we aimed to analyse factors associated with ever having a CS using the 2019 National Multiple Indicator Cluster Survey. The weighted national CS rate was 10.3%, and CS happened more commonly among women in urban than rural areas (15.7% v. 7.4%; odds ratio (OR) 2.34; (95% confidence interval (CI)) 1.71 - 3.20; p=0.001). Percentages of those having a CS significantly increased with education: overall χ2 for a trend of p=0.001 and wealth quintile, and overall χ2 for a trend of p=0.001. Women with insurance coverage were more likely to have had a CS than those without: 26.7% v. 8.7%; OR 3.82; 95% CI 2.51 - 5.83; p=0.001. The same was the case for women with access to the internet: 15.4% v. 7.0%, OR 2.42; 95%CI 1.71 - 3.41; p=0.001). These findings show an association that could indicate this being overutilised by insured women in urban settings, rather than being accessible based on clinical needs. Further research should explore reasons for these disparities and inform interventions to ensure equitable access to optimum childbirth in Zimbabwe.

Background: Understanding the pattern of contraceptive use among women living with HIV is critical for formulating relevant public health interventions to improve the uptake and use of reliable methods in this population. This helps to reduce the incidence of unintended pregnancies., Objective: In this secondary data analysis, we aimed to describe contraceptive use by HIV-positive and HIV-negative sexually active adolescent girls and women, using data from the Zimbabwe Demographic and Health Survey (2015-16)., Method: We used statistical analysis to determine the association between the use of various methods of contraception and HIV status using the Zimbabwe Demographic and Health Survey, 2015-16 data., Results: Overall, the contraceptive use prevalence in this study was 60%. Sexually active adolescent girls and women on the Pill and injections were less likely to be HIV-positive compared with those not using any method of contraception (odds ratio (OR)=0.54, 95% confidence interval (CI) (0.45 - 0.64), p=0.001; and OR=0.75, 95% CI (0.59 - 0.96), p=0.020, respectively). Those using either a male or female condom were more likely to be HIV-positive, OR=3.36, 95% CI (2.63 - 4.28), p=0.001., Conclusions: This study revealed that there is still a considerable unmet need for contraception among the study population, highlighting the need to devise strategies to increase contraception uptake among women. Statistically significant differences were noted in the use of condoms, with those who are HIV-positive having a higher use of condoms compared with those who are HIV-negative. This may reflect that HIV-positive individuals have received appropriate counselling messages on the need to use barrier methods.

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.

Acute myocarditis (AM) in early pregnancy is a rare disease. Its clinical presentation varies from asymptomatic disease to cardiogenic shock and death. A 28-year-old woman, 12 weeks primigravida of a dichorionic and diamniotic pregnancy, was admitted for hyperemesis gravidarum, associated with a common cold-like condition. During hospitalization, she developed new-onset sinus tachycardia and dyspnea. An electrocardiogram revealed sinus tachycardia and diffuse ST-segment elevation. Laboratory tests showed elevated levels of troponin and pro-B-type natriuretic peptide. Pelvic obstetric ultrasound and chest X-ray were normal. Speckle-tracking echocardiography showed mild apical hypokinesia with preserved left ventricular ejection fraction. In view of these findings, AM was suspected, and cardiac magnetic resonance imaging was highly suggestive of AM. The patient had a favorable recovery without cardiovascular or obstetric complications., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2023, Flores-Sanga et al.)

Despite the scale-up of antiretroviral therapy (ART) in South Africa, HIV-1 incidence remains high. The anticipated use of potent integrase strand transfer inhibitors and long-acting injectables aims to enhance viral suppression at the population level and diminish transmission. Nevertheless, pre-existing drug resistance could impede the efficacy of long-acting injectable ART combinations, such as rilpivirine (an NNRTI) and cabotegravir (an INSTI). Consequently, a thorough understanding of transmission networks and geospatial distributions is vital for tailored interventions, including pre-exposure prophylaxis with long-acting injectables. However, empirical data on background resistance and transmission networks remain limited. In a community-based study in rural KwaZulu-Natal (2018-2019), prior to the widespread use of integrase inhibitor-based first-line ART, we performed HIV testing with reflex HIV-1 RNA viral load quantification on 18,025 participants. From this cohort, 6,096 (33.9%) tested positive for HIV via ELISA, with 1,323 (21.7%) exhibiting detectable viral loads (> 40 copies/mL). Of those with detectable viral loads, 62.1% were ART-naïve, and the majority of the treated were on an efavirenz + cytosine analogue + tenofovir regimen. Deep sequencing analysis, with a variant abundance threshold of 20%, revealed NRTI resistance mutations such as M184V in 2% of ART-naïve and 32% of treated individuals. Tenofovir resistance mutations K65R and K70E were found in 12% and 5% of ART-experienced individuals, respectively, and in less than 1% of ART-naïve individuals. Integrase inhibitor resistance mutations were notably infrequent (< 1%). Prevalence of pre-treatment drug resistance to NNRTIs was 10%, predominantly consisting of the K103N mutation. Among those with viraemic ART, NNRTI resistance was 50%, with rilpivirine-associated mutations observed in 9% of treated and 6% of untreated individuals. Cluster analysis revealed that 20% (205/1,050) of those sequenced were part of a cluster. We identified 171 groups with at least two linked participants; three quarters of clusters had only two individuals, and a quarter had 3-6 individuals. Integrating phylogenetic with geospatial analyses, we revealed a complex transmission network with significant clustering in specific regions, notably peripheral and rural areas. These findings derived from population scale genomic analyses are encouraging in terms of the limited resistance to DTG, but indicate that transitioning to long-acting cabotegravir + rilpivirine for transmission reduction should be accompanied by prior screening for rilpivirine resistance. Whole HIV-1 genome sequencing allowed identification of significant proportions of clusters with multiple individuals, and geospatial analyses suggesting decentralised networks can inform targeting public health interventions to effectively curb HIV-1 transmission.

Competing Interests: GM was employed by International Initiative for Impact Evaluation. The remaining 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.

The COVID-19 pandemic has dramatically altered people's lives in multiple aspects, including grocery shopping behaviors. Yet, the changing trend of grocery shopping frequencies during the COVID-19 and its associations with food deserts remain unclear. We aimed to (1) examine variations of grocery shopping frequencies at county level in the USA during the COVID-19 pandemic from March 2020 to December 2021; (2) investigate associations between grocery shopping frequencies and food deserts during the COVID-19 pandemic; and (3) explore heterogeneity in grocery shopping frequencies-food desert associations across urban and rural areas. The county-level grocery shopping frequencies were derived from a grocery pattern dataset obtained from SafeGraph. We divided the 22-month period into 5 stages and employed the growth curve modeling to estimate the trajectories of grocery shopping frequencies and the associations between grocery shopping frequencies and food deserts in each stage, separately. Results revealed that grocery shopping frequencies experienced a "W-shaped" pattern from March 2020 to December 2021. Counties with the least percent of food deserts had slower decrease in grocery shopping frequencies at the initial stage and recovered more rapidly at later stages. Counties with the highest percent of food deserts were subject to deprivation amplification as a result of the pandemic. We also found differences existed in the grocery shopping frequencies-food desert associations between metropolitan counties and rural counties. Our findings suggest the impacts of COVID-19 on grocery shopping frequencies varied across different time periods, shedding light on designing different strategies to reduce the risk of contagion while shopping inside of grocery stores. Further, our findings highlight an urgent need to help people living in food deserts (especially in rural counties) to procure healthy foods safely during health emergencies like COVID-19 pandemic which disrupt mobility and social behaviors., (© 2023. The New York Academy of Medicine.)

Background: The convergence of infectious diseases and non-communicable diseases in South Africa is challenging to health systems. In this analysis, we assessed the multimorbidity health needs of individuals and communities in rural KwaZulu-Natal and established a framework to quantify met and unmet health needs for individuals living with infectious and non-communicable diseases., Methods: We analysed data collected between May 25, 2018, and March 13, 2020, from participants of a large, community-based, cross-sectional multimorbidity survey (Vukuzazi) that offered community-based HIV, hypertension, and diabetes screening to all residents aged 15 years or older in a surveillance area in the uMkhanyakude district in KwaZulu-Natal, South Africa. Data from the Vukuzazi survey were linked with data from demographic and health surveillance surveys with a unique identifier common to both studies. Questionnaires were used to assess the diagnosed health conditions, treatment history, general health, and sociodemographic characteristics of an individual. For each condition (ie, HIV, hypertension, and diabetes), individuals were defined as having no health needs (absence of condition), met health needs (condition that is well controlled), or one or more unmet health needs (including diagnosis, engagement in care, or treatment optimisation). We analysed met and unmet health needs for individual and combined conditions and investigated their geospatial distribution., Findings: Of 18 041 participants who completed the survey (12 229 [67·8%] were female and 5812 [32·2%] were male), 9898 (54·9%) had at least one of the three chronic diseases measured. 4942 (49·9%) of these 9898 individuals had at least one unmet health need (1802 [18·2%] of 9898 needed treatment optimisation, 1282 [13·0%] needed engagement in care, and 1858 [18·8%] needed a diagnosis). Unmet health needs varied by disease; 1617 (93·1%) of 1737 people who screened positive for diabetes, 2681 (58·2%) of 4603 people who screened positive for hypertension, and 1321 (21·7%) of 6096 people who screened positive for HIV had unmet health needs. Geospatially, met health needs for HIV were widely distributed and unmet health needs for all three conditions had specific sites of concentration; all three conditions had an overlapping geographical pattern for the need for diagnosis., Interpretation: Although people living with HIV predominantly have a well controlled condition, there is a high burden of unmet health needs for people living with hypertension and diabetes. In South Africa, adapting current, widely available HIV care services to integrate non-communicable disease care is of high priority., Funding: Fogarty International Center and the National Institutes of Health, the Bill & Melinda Gates Foundation, the South African Department of Science and Innovation, the South African Medical Research Council, the South African Population Research Infrastructure Network, and the Wellcome Trust., Translation: For the isiZulu translation of the abstract see Supplementary Materials section., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

The convergence of infectious and non-communicable diseases (NCDs) in South Africa poses a challenge to health systems. Here we establish a framework to quantify met and unmet health needs for individuals living with infectious and NCDs. In this study, we screened adult residents >15 years of age within the uMkhanyakude district in KwaZulu- Natal, South Africa for HIV, hypertension (HPTN) and diabetes mellitus (DM). For each condition, individuals were defined as having no unmet health needs (absence of condition), met health need (condition that is well controlled), or one or more unmet health needs (including diagnosis, engagement in care, or treatment optimization). We analyzed met and unmet health needs for individual and combined conditions and investigated their geospatial distribution. We found that of 18,041 participants, 9,898 (55%) had at least one chronic condition. 4,942 (50%) of these individuals had at least one unmet health need (18% needed treatment optimization, 13% needed engagement in care, and 19% needed diagnosis). Unmet health needs varied by disease: 93% of people with DM, 58% of people with HPTN and 21% of people with HIV had unmet health needs. Geospatially, met health needs for HIV were widely distributed, unmet health needs had specific sites of concentration whilst the need for diagnosis for all three conditions was co-located. Whilst people living with HIV are predominantly well-controlled, there is a high burden of unmet health needs for people living with HPTN and DM. Adaptation of HIV models of care to integrate HIV and NCD services is of high priority.

Background: Accurate human immunodeficiency virus (HIV) risk assessment can guide optimal HIV prevention. We evaluated the performance of risk prediction models incorporating geospatial measures., Methods: We developed and validated HIV risk prediction models in a population-based cohort in South Africa. Individual-level covariates included demographic and sexual behavior measures, and geospatial covariates included community HIV prevalence and viral load estimates. We trained models on 2012-2015 data using LASSO Cox models and validated predictions in 2016-2019 data. We compared full models to simpler models restricted to only individual-level covariates or only age and geospatial covariates. We compared the spatial distribution of predicted risk to that of high incidence areas (≥ 3/100 person-years)., Results: Our analysis included 19 556 individuals contributing 44 871 person-years and 1308 seroconversions. Incidence among the highest predicted risk quintile using the full model was 6.6/100 person-years (women) and 2.8/100 person-years (men). Models using only age group and geospatial covariates had similar performance (women: AUROC = 0.65, men: AUROC = 0.71) to the full models (women: AUROC = 0.68, men: AUROC = 0.72). Geospatial models more accurately identified high incidence regions than individual-level models; 20% of the study area with the highest predicted risk accounted for 60% of the high incidence areas when using geospatial models but only 13% using models with only individual-level covariates., Conclusions: Geospatial models with no individual measures other than age group predicted HIV risk nearly as well as models that included detailed behavioral data. Geospatial models may help guide HIV prevention efforts to individuals and geographic areas at highest risk., Competing Interests: Potential conflicts of interest. R. V. B. reports grants from the Bill & Melinda Gates Foundation (BMGF) and the NIH; participation on a Data Safety Monitoring Board or Advisory Board for HIV Vaccine Trials Network (HVTN), University of California, San Francisco (USCF), and London School of Hygiene & Tropical Medicine (LSHTM); and Regeneron Pharmaceuticals for conference abstract and manuscript writing support, outside the submitted work. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2022. Published by Oxford University Press for the Infectious Diseases Society of America.)

HIV and AIDS continue to be major public health concerns globally. Despite significant progress in addressing their impact on the general population and achieving epidemic control, there is a need to improve HIV testing, particularly among men who have sex with men (MSM). This study applied deep and machine learning algorithms such as recurrent neural networks (RNNs), the bagging classifier, gradient boosting classifier, support vector machines, and Naïve Bayes classifier to predict HIV status among MSM using the dataset from the Zimbabwe Ministry of Health and Child Care. RNNs performed better than the bagging classifier, gradient boosting classifier, support vector machines, and Gaussian Naïve Bayes classifier in predicting HIV status. RNNs recorded a high prediction accuracy of 0.98 as compared to the Gaussian Naïve Bayes classifier (0.84), bagging classifier (0.91), support vector machine (0.91), and gradient boosting classifier (0.91). In addition, RNNs achieved a high precision of 0.98 for predicting both HIV-positive and -negative cases, a recall of 1.00 for HIV-negative cases and 0.94 for HIV-positive cases, and an F1-score of 0.99 for HIV-negative cases and 0.96 for positive cases. HIV status prediction models can significantly improve early HIV screening and assist healthcare professionals in effectively providing healthcare services to the MSM community. The results show that integrating HIV status prediction models into clinical software systems can complement indicator condition-guided HIV testing strategies and identify individuals that may require healthcare services, particularly for hard-to-reach vulnerable populations like MSM. Future studies are necessary to optimize machine learning models further to integrate them into primary care. The significance of this manuscript is that it presents results from a study population where very little information is available in Zimbabwe due to the criminalization of MSM activities in the country. For this reason, MSM tends to be a hidden sector of the population, frequently harassed and arrested. In almost all communities in Zimbabwe, MSM issues have remained taboo, and stigma exists in all sectors of society.

Introduction: the objective of this manuscript was to describe the knowledge profiles and determinants of cervical cancer screening among HIV positive and negative adolescent girls and women in Zimbabwe., Methods: we conducted secondary statistical data analysis to explore the determinants of cervical cancer screening among HIV positive and negative adolescent girls and women using Zimbabwe Demographic Health survey for 2015-16., Results: a total of 9054 adolescent girls aged 15-19, and women aged 20-49 were included in the analysis and the majority (63%) of them resided in rural areas. More than two-thirds (65.9%) had attained secondary level of education. The majority (41.3%) of the adolescent girls and women belonged to the Apostolic sect. A number of key determinants have been identified for being ever screened for cervical cancer. The odds of being ever being screened increased by age, OR(CI) 4.38 (3.22-5.94), p<0.001 for women who are 40 years and older when compared to adolescent and young woman who are between 15-24 years., Conclusion: our study reports significant programmatic gaps in the provision of cervical cancer screening and treatment services in the country. The nascent Zimbabwe cervical cancer screening and treatment progamme will benefit from expansion of the number of facilities offering the services and the provision of more efficient health education to adolescent women and girls., Competing Interests: The authors declare no competing interests., (Copyright: Godfrey Musuka et al.)

Understanding spatial configuration of sexual network structure is critical for effective use of HIV preventative interventions in a community. However, this has never been described at the population level for any setting in sub-Saharan Africa. We constructed the comprehensive geospatial sexual network among new heterosexual partnerships in rural KwaZulu-Natal, South Africa. In the Africa Health Research Institute (AHRI)'s population-based surveillance, we identified stable sexual partnerships among individuals (≥15 years) from 2003 to 2016. Sexual partnerships and residency were recorded via household surveys (every 4-6 months). We geolocated residents and migration events and mapped the geospatial linkages of sexual partners at the start of sexual partnerships. In a grid composed by 108 cells (nodes; 3kmx3km per cell) covering the surveillance area (438km2), we calculated the degree of connectivity and centrality of the nodes and examined their association with HIV prevalence and incidence per cell. Of 2401 new sexual partnerships, 21% (n = 495) had both partners living within the surveillance area at the start of sexual partnerships, and 76% (376/495) were linked to the geographic HIV cluster with high HIV prevalence identified in a peri-urban community. Overall, 57 nodes had at least one connection to another node. The nodes in the peri-urban cluster had higher connectivity (mean = 19, range: 9-32), compared to outside the cluster (6, range: 1-16). The node's degree of connectivity was positively associated with HIV prevalence of the cell (Pearson correlation coefficient = 0.67; p <0.005). The peri-urban cluster contained nine of the 10 nodes that composed of a single large central module in the community. About 17% of sexual partnerships (n = 421) were formed between a resident and a non-resident partner who out-migrated. Most of these non-resident partners lived in KwaZulu-Natal (86.7%), followed by Gauteng (9.7%), and the median distance between a resident and a non-resident partner was 50.1km (IQR: 23.2-177.2). We found that the peri-urban HIV cluster served as the highly connected central node of the network for sexual partnership formation. The network was also connected beyond the surveillance area across South Africa. Understanding spatial sexual network can improve the provision of spatially targeted and effective interventions., Competing Interests: All authors have no conflict of interests to report., (Copyright: © 2022 Kim 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.)

The COVID-19 pandemic has disrupted the learning of millions of children across the world. Since March 2020 when the first cases of COVID-19 were reported in Zimbabwe, the country, like many others, has gone through periods of closing and re-opening of schools as part of the national COVID-19 control and mitigation measures. Schools promote the social, mental, physical, and moral development of children. With this viewpoint, the authors argue that schools should not be closed to provide a measured and efficient response to the threats posed by the COVID-19 epidemic. Rather, infection prevention and control strategies, including vaccination of learners and teachers, and surveillance in schools should be heightened. The use of multiple prevention strategies discussed in this viewpoint has shown that when outbreaks in school settings are adequately managed, the transmission usually is low. The information presented here suggests that schools should remain open due to the preponderance of evidence indicating the overriding positive impacts of this policy on the health, development, and wellbeing of children.