Prevention and control of Ebola virus transmission: mathematical modelling and data fitting.

The Ebola virus disease (EVD) has been endemic since 1976, and the case fatality rate is extremely high. EVD is spread by infected animals, symptomatic individuals, dead bodies, and contaminated environment. In this paper, we formulate an EVD model with four transmission modes and a time delay describing the incubation period. Through dynamical analysis, we verify the importance of blocking the infection source of infected animals. We get the basic reproduction number without considering the infection source of infected animals. And, it is proven that the model has a globally attractive disease-free equilibrium when the basic reproduction number is less than unity; the disease eventually becomes endemic when the basic reproduction number is greater than unity. Taking the EVD epidemic in Sierra Leone in 2014-2016 as an example, we complete the data fitting by combining the effect of the media to obtain the unknown parameters, the basic reproduction number and its time-varying reproduction number. It is shown by parameter sensitivity analysis that the contact rate and the removal rate of infected group have the greatest influence on the prevalence of the disease. And, the disease-controlling thresholds of these two parameters are obtained. In addition, according to the existing vaccination strategy, only the inoculation ratio in high-risk areas is greater than 0.4, the effective reproduction number can be less than unity. And, the earlier the vaccination time, the greater the inoculation ratio, and the faster the disease can be controlled.

Epidemic spreading on spatial higher-order network.

Higher-order interactions exist widely in mobile populations and are extremely important in spreading epidemics, such as influenza. However, research on high-order interaction modeling of mobile crowds and the propagation dynamics above is still insufficient. Therefore, this study attempts to model and simulate higher-order interactions among mobile populations and explore their impact on epidemic transmission. This study simulated the spread of the epidemic in a spatial high-order network based on agent-based model modeling. It explored its propagation dynamics and the impact of spatial characteristics on it. Meanwhile, we construct state-specific rate equations based on the uniform mixing assumption for further analysis. We found that hysteresis loops are an inherent feature of high-order networks in this space under specific scenarios. The evolution curve roughly presents three different states with the initial value change, showing different levels of the endemic balance of low, medium, and high, respectively. Similarly, network snapshots and parameter diagrams also indicate these three types of equilibrium states. Populations in space naturally form components of different sizes and isolations, and higher initial seeds generate higher-order interactions in this spatial network, leading to higher infection densities. This phenomenon emphasizes the impact of high-order interactions and high-order infection rates in propagation. In addition, crowd density and movement speed act as protective and inhibitory factors for epidemic transmission, respectively, and depending on the degree of movement weaken or enhance the effect of hysteresis loops.

Forecasting and mapping dengue fever epidemics in China: a spatiotemporal analysis.

BACKGROUND: Dengue fever (DF) has emerged as a significant public health concern in China. The spatiotemporal patterns and underlying influencing its spread, however, remain elusive. This study aims to identify the factors driving these variations and to assess the city-level risk of DF epidemics in China. METHODS: We analyzed the frequency, intensity, and distribution of DF cases in China from 2003 to 2022 and evaluated 11 natural and socioeconomic factors as potential drivers. Using the random forest (RF) model, we assessed the contributions of these factors to local DF epidemics and predicted the corresponding city-level risk. RESULTS: Between 2003 and 2022, there was a notable correlation between local and imported DF epidemics in case numbers (r = 0.41, P < 0.01) and affected cities (r = 0.79, P < 0.01). With the increase in the frequency and intensity of imported epidemics, local epidemics have become more severe. Their occurrence has increased from five to eight months per year, with case numbers spanning from 14 to 6641 per month. The spatial distribution of city-level DF epidemics aligns with the geographical divisions defined by the Huhuanyong Line (Hu Line) and Qin Mountain-Huai River Line (Q-H Line) and matched well with the city-level time windows for either mosquito vector activity (83.59%) or DF transmission (95.74%). The RF models achieved a high performance (AUC = 0.92) when considering the time windows. Importantly, they identified imported cases as the primary influencing factor, contributing significantly (24.82%) to local DF epidemics at the city level in the eastern region of the Hu Line (E-H region). Moreover, imported cases were found to have a linear promoting impact on local epidemics, while five climatic and six socioeconomic factors exhibited nonlinear effects (promoting or inhibiting) with varying inflection values. Additionally, this model demonstrated outstanding accuracy (hitting ratio = 95.56%) in predicting the city-level risks of local epidemics in China. CONCLUSIONS: China is experiencing an increasing occurrence of sporadic local DF epidemics driven by an unavoidably higher frequency and intensity of imported DF epidemics. This research offers valuable insights for health authorities to strengthen their intervention capabilities against this disease.

Estimating the potential value of MSM-focused evidence-based implementation interventions in three Ending the HIV Epidemic jurisdictions in the United States: a model-based analysis.

INTRODUCTION: Improving the delivery of existing evidence-based interventions to prevent and diagnose HIV is key to Ending the HIV Epidemic in the United States. Structural barriers in the access and delivery of related health services require municipal or state-level policy changes; however, suboptimal implementation can be addressed directly through interventions designed to improve the reach, effectiveness, adoption or maintenance of available interventions. Our objective was to estimate the cost-effectiveness and potential epidemiological impact of six real-world implementation interventions designed to address these barriers and increase the scale of delivery of interventions for HIV testing and pre-exposure prophylaxis (PrEP) in three US metropolitan areas. METHODS: We used a dynamic HIV transmission model calibrated to replicate HIV microepidemics in Atlanta, Los Angeles (LA) and Miami. We identified six implementation interventions designed to improve HIV testing uptake ("Academic detailing for HIV testing," "CyBER/testing," "All About Me") and PrEP uptake/persistence ("Project SLIP," "PrEPmate," "PrEP patient navigation"). Our comparator scenario reflected a scale-up of interventions with no additional efforts to mitigate implementation and structural barriers. We accounted for potential heterogeneity in population-level effectiveness across jurisdictions. We sustained implementation interventions over a 10-year period and evaluated HIV acquisitions averted, costs, quality-adjusted life years and incremental cost-effectiveness ratios over a 20-year time horizon (2023-2042). RESULTS: Across jurisdictions, implementation interventions to improve the scale of HIV testing were most cost-effective in Atlanta and LA (CyBER/testing cost-saving and All About Me cost-effective), while interventions for PrEP were most cost-effective in Miami (two of three were cost-saving). We estimated that the most impactful HIV testing intervention, CyBER/testing, was projected to avert 111 (95% credible interval: 110-111), 230 (228-233) and 101 (101-103) acquisitions over 20 years in Atlanta, LA and Miami, respectively. The most impactful implementation intervention to improve PrEP engagement, PrEPmate, averted an estimated 936 (929-943), 860 (853-867) and 2152 (2127-2178) acquisitions over 20 years, in Atlanta, LA and Miami, respectively. CONCLUSIONS: Our results highlight the potential impact of interventions to enhance the implementation of existing evidence-based interventions for the prevention and diagnosis of HIV.

Is HIV epidemic control by 2030 realistic?

Rates of new HIV acquisition remain unacceptably high in most populations in low-income, middle-income, and high-income settings despite advances in treatment and prevention strategies. Although biomedical advances in primary prevention of new infections exist, systematic scale-up of these interventions has not occurred at the pace required to end AIDS by 2030. Low population coverage, adherence to oral pre-exposure prophylaxis in settings with high rates of HIV acquisition, and the fact that a significant proportion of new HIV infections occurs in populations not identified as high risk and are hence not targeted for prevention approaches impedes current prevention strategies. Although long-acting injectables and monoclonal antibodies are promising approaches to help reduce incidence, high cost and the need for high coverage rates mean that a vaccine or vaccine-like intervention still remains the most likely scenario to produce a population-level impact on HIV incidence, especially in countries with generalised epidemics. Current global efforts are not sufficient to meet 2030 HIV epidemic goals; acknowledgment of this issue is required to ensure persistent advocacy for population-based control of the ongoing HIV pandemic.

Optimization of "vehicle-UAV" joint distribution routing for cold chain logistics considering risk of epidemic spreading and green cost.

To address the epidemic, such as COVID-19, the government may implement the home quarantine policy for the infected residents. The logistics company is required to control the risk of epidemic spreading while delivering goods to residents. In this case, the logistics company often uses vehicles and unmanned aerial vehicles (UAVs) for delivery. This paper studies the distribution issue of cold chain logistics by integrating UAV logistics with epidemic risk management innovatively. At first, a "vehicle-UAV" joint distribution mode including vehicles, small UAVs and large UAVs, is proposed. The green cost for vehicles and UAVs is calculated, respectively. The formula for infection risk due to large numbers of residents gathering at distribution centers to pick up goods is then derived. Furthermore, based on the control of infection risk, an optimization model is developed to minimize the total logistics cost. A modified ant colony algorithm is designed to solve the model. The numerical results show that the maximum acceptable risk and the crowd management level of distribution centers both have significant effects on the distribution network, logistics cost and number of new infections. Our study provides a new management method and technical idea for ensuring the needs of residents during the epidemic.

An innovative fractional-order evolutionary game theoretical study of personal protection, quarantine, and isolation policies for combating epidemic diseases.

This study uses imposed control techniques and vaccination game theory to study disease dynamics with transitory or diminishing immunity. Our model uses the ABC fractional-order derivative mechanism to show the effect of non-pharmaceutical interventions such as personal protection or awareness, quarantine, and isolation to simulate the essential control strategies against an infectious disease spread in an infinite and uniformly distributed population. A comprehensive evolutionary game theory study quantified the significant influence of people's vaccination choices, with government forces participating in vaccination programs to improve obligatory control measures to reduce epidemic spread. This model uses the intervention options described above as a control strategy to reduce disease prevalence in human societies. Again, our simulated results show that a combined control strategy works exquisitely when the disease spreads even faster. A sluggish dissemination rate slows an epidemic outbreak, but modest control techniques can reestablish a disease-free equilibrium. Preventive vaccination regulates the border between the three phases, while personal protection, quarantine, and isolation methods reduce disease transmission in existing places. Thus, successfully combining these three intervention measures reduces epidemic or pandemic size, as represented by line graphs and 3D surface diagrams. For the first time, we use a fractional-order derivate to display the phase-portrayed trajectory graph to show the model's dynamics if immunity wanes at a specific pace, considering various vaccination cost and effectiveness settings.

One Health Risk and Disease (OHRAD): a tool to prioritise the risks for epidemic-prone diseases from One Health perspective.

BACKGROUND: The rise in epidemic-prone diseases daily poses a serious concern globally. Evidence suggests that many of these diseases are of animal origin and contribute to economic loss. Considering the limited time and other resources available for the animal and human health sectors, selecting the most urgent and significant risk factors and diseases is vital, even though all epidemic-prone diseases and associated risk factors should be addressed. The main aim of developing this tool is to provide a readily accessible instrument for prioritising risk factors and diseases that could lead to disease emergence, outbreak or epidemic. METHODS: This tool uses a quantitative and semi-quantitative multi-criteria decision analysis (MCDA) method that involves five steps: Identifying risk factors and diseases, Weighting the criteria, Risk and disease scoring, Calculating risk impact and disease burden score, and Ranking risks and diseases. It is intended to be implemented through a co-creation workshop and involves individual and group activities. The last two steps are automated in the MS Excel score sheet. RESULTS: This One Health Risk and Disease (OHRAD) prioritisation tool starts with an individual activity of identifying the risks and diseases from the more extensive list. This, then, leads to a group activity of weighing the criteria and providing scores for each risk and disease. Finally, the individual risk and disease scores with the rankings are generated in this tool. CONCLUSIONS: The outcome of this OHRAD prioritisation tool is that the top risks and diseases are prioritised for the particular context from One Health perspective. This prioritised list will help experts and officials decide which epidemic-prone diseases to focus on and for which to develop and design prevention and control measures.

Regional differences of Mycobacterium tuberculosis complex infection and multidrug resistance epidemic in Luoyang.

BACKGROUND: Tuberculosis (TB) remains a global public health event of great concern, however epidemic data on TB covering entire areas during the special period of the COVID-19 epidemic have rarely been reported. We compared the dissemination and multidrug-resistance patterns of Mycobacterium tuberculosis complex (MTBC) in the main urban area of Luoyang City, China (including six municipal jurisdictions) and nine county and township areas under its jurisdiction, aimed to establish the epidemiology of TB in this region and to provide reference for precision anti-TB in places with similar settings. METHODS: From 2020 to 2022, sputum samples were collected from 18,504 patients with confirmed, suspected and unexcluded TB in 10 designated TB medical institutions. Insertion sequence 6110 was amplified by PCR (rpoB gene detection if necessary) to confirm the presence of MTBC. PCR-positive specimens were analyzed by multicolor melting curve analysis to detect multidrug resistance. RESULTS: Among the 18,504 specimens, 2675 (14.5%) were MTBC positive. The positive rate was higher in the main urban area than in the county and township areas (29.8% vs. 10.9%, p < 0.001). Male, re-treated and smear-positive groups were high-burden carriers of MTBC. Individuals aged > 60 years were the largest group infected with MTBC in the main urban area, compared with individuals aged < 61 years in the county and township areas. The detection of multidrug-resistant TB (MDR-TB) was higher in the main urban area than in the county and township areas (13.9% vs. 7.8%, p < 0.001). In all areas, MDR-TB groups were dominated by males, patients with a history of TB treatment, and patients aged < 61 years. Stratified analysis of MDR-TB epidemiology showed that MDR4 (INH þ RIF þ EMB þ SM) was predominant in the main urban area, while MDR3 (INH þ RIF þ SM) was predominant in the county and township areas. MDR-TB detection rate and epidemiology differed among the county and township areas. CONCLUSIONS: For local TB control, it is necessary to plan more appropriate and accurate prevention and control strategies according to the regional distribution of MTBC infection.

Epidemic of parvovirus B19 and disease severity in pregnant people, Denmark, January to March 2024.

We report an epidemic of parvovirus B19 infections in Denmark during the first quarter of 2024, with a peak incidence 3.5 times higher than during the most recent epidemic in 2017. In total, 20.1% (130/648) of laboratory-confirmed cases were pregnant. Severe adverse outcomes were observed among 12.3% (16/130) of pregnant people and included foetal anaemia, foetal hydrops and miscarriage. Parvovirus B19 infection is not systematically monitored, but a national laboratory-based surveillance system is currently being established in Denmark.

Evolutionary Invasion Analysis of Modern Epidemics Highlights the Context-Dependence of Virulence Evolution.

Models are often employed to integrate knowledge about epidemics across scales and simulate disease dynamics. While these approaches have played a central role in studying the mechanics underlying epidemics, we lack ways to reliably predict how the relationship between virulence (the harm to hosts caused by an infection) and transmission will evolve in certain virus-host contexts. In this study, we invoke evolutionary invasion analysis-a method used to identify the evolution of uninvadable strategies in dynamical systems-to examine how the virulence-transmission dichotomy can evolve in models of virus infections defined by different natural histories. We reveal peculiar patterns of virulence evolution between epidemics with different disease natural histories (SARS-CoV-2 and hepatitis C virus). We discuss the findings with regards to the public health implications of predicting virus evolution, and in broader theoretical canon involving virulence evolution in host-parasite systems.

Space-time dispersion of dengue occurrence in epidemic and non-epidemic years in a municipality in the metropolitan region of Belo Horizonte, MG, 2011 to 2017.

OBJECTIVE: To analyze the transmission dynamics of dengue, a public health problem in Brazil and the Metropolitan Region of Belo Horizonte (MRBH). METHODS: The spatiotemporal evolution of the occurrence of dengue in the municipality of Contagem, state of Minas Gerais, a region with high arbovirus transmission, was analyzed. Furthermore, epidemic and non-epidemic periods were analyzed, based on probable cases of dengue. This is an ecological study that used the Notifiable Diseases Information System (SINAN) national database. The analyses were carried out considering the period from epidemiological week (EW) 40 of 2011 to 39 of 2017. Spatial analysis tools (crude and smoothed incidence rate, directional distribution ellipse, global Moran index and local Moran index, and spatial scanning time with definition of epidemiological risk) were used. RESULTS: The 2012 to 2013 and 2015 to 2016 epidemic cycles presented high incidence rates. The disease was concentrated in more urbanized areas, with a small increase in cases throughout the municipality. Seven statistically significant local clusters and areas with a high rate of cases and accentuated transmission in epidemic cycles were observed throughout the municipality. Spatial autocorrelation of the incidence rate was observed in all periods. CONCLUSION: The results of the present study highlight a significant and heterogeneous increase in dengue notifications in Contagem over the years, revealing distinct spatial patterns during epidemic and non-epidemic periods. Geoprocessing analysis identified high-risk areas, a piece of knowledge that can optimize the allocation of resources in the prevention and treatment of the disease for that municipality.

The impact of temperature, humidity and closing school on the mumps epidemic: a case study in the mainland of China.

BACKGROUND: To control resurging infectious diseases like mumps, it is necessary to resort to effective control and preventive measures. These measures include increasing vaccine coverage, providing the community with advice on how to reduce exposure, and closing schools. To justify such intervention, it is important to understand how well each of these measures helps to limit transmission. METHODS: In this paper, we propose a simple SEILR (susceptible-exposed-symptomatically infectious-asymptomatically infectious-recovered) model by using a novel transmission rate function to incorporate temperature, humidity, and closing school factors. This new transmission rate function allows us to verify the impact of each factor either separately or combined. Using reported mumps cases from 2004 to 2018 in the mainland of China, we perform data fitting and parameter estimation to evaluate the basic reproduction number  R 0 . As a wide range of one-dose measles, mumps, and rubella (MMR) vaccine programs in China started only in 2008, we use different vaccination proportions for the first Stage I period (from 2004 to 2008) and the second Stage II period (from 2009 to 2018). This allows us to verify the importance of higher vaccine coverage with a possible second dose of MMR vaccine. RESULTS: We find that the basic reproduction number  R 0  is generally between 1 and 3. We then use the Akaike Information Criteria to assess the extent to which each of the three factors contributed to the spread of mumps. The findings suggest that the impact of all three factors is substantial, with temperature having the most significant impact, followed by school opening and closing, and finally humidity. CONCLUSION: We conclude that the strategy of increasing vaccine coverage, changing micro-climate (temperature and humidity), and closing schools can greatly reduce mumps transmission.

The influence of cross-border mobility on the COVID-19 epidemic in Nordic countries.

Restrictions of cross-border mobility are typically used to prevent an emerging disease from entering a country in order to slow down its spread. However, such interventions can come with a significant societal cost and should thus be based on careful analysis and quantitative understanding on their effects. To this end, we model the influence of cross-border mobility on the spread of COVID-19 during 2020 in the neighbouring Nordic countries of Denmark, Finland, Norway and Sweden. We investigate the immediate impact of cross-border travel on disease spread and employ counterfactual scenarios to explore the cumulative effects of introducing additional infected individuals into a population during the ongoing epidemic. Our results indicate that the effect of inter-country mobility on epidemic growth is non-negligible essentially when there is sizeable mobility from a high prevalence country or countries to a low prevalence one. Our findings underscore the critical importance of accurate data and models on both epidemic progression and travel patterns in informing decisions related to inter-country mobility restrictions.

Dynamics of simplicial SEIRS epidemic model: global asymptotic stability and neural Lyapunov functions.

The transmission of infectious diseases on a particular network is ubiquitous in the physical world. Here, we investigate the transmission mechanism of infectious diseases with an incubation period using a networked compartment model that contains simplicial interactions, a typical high-order structure. We establish a simplicial SEIRS model and find that the proportion of infected individuals in equilibrium increases due to the many-body connections, regardless of the type of connections used. We analyze the dynamics of the established model, including existence and local asymptotic stability, and highlight differences from existing models. Significantly, we demonstrate global asymptotic stability using the neural Lyapunov function, a machine learning technique, with both numerical simulations and rigorous analytical arguments. We believe that our model owns the potential to provide valuable insights into transmission mechanisms of infectious diseases on high-order network structures, and that our approach and theory of using neural Lyapunov functions to validate model asymptotic stability can significantly advance investigations on complex dynamics of infectious disease.

Epidemic Characteristics and Meteorological Risk Factors of Hemorrhagic Fever With Renal Syndrome in 151 Cities in China From 2015 to 2021: Retrospective Analysis.

BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS) continues to pose a significant public health threat to the population in China. Previous epidemiological evidence indicates that HFRS is climate sensitive and influenced by meteorological factors. However, past studies either focused on too-narrow geographical regions or investigated time periods that were too early. There is an urgent need for a comprehensive analysis to interpret the epidemiological patterns of meteorological factors affecting the incidence of HFRS across diverse climate zones. OBJECTIVE: In this study, we aimed to describe the overall epidemic characteristics of HFRS and explore the linkage between monthly HFRS cases and meteorological factors at different climate levels in China. METHODS: The reported HFRS cases and meteorological data were collected from 151 cities in China during the period from 2015 to 2021. We conducted a 3-stage analysis, adopting a distributed lag nonlinear model and a generalized additive model to estimate the interactions and marginal effects of meteorological factors on HFRS. RESULTS: This study included a total of 63,180 cases of HFRS; the epidemic trends showed seasonal fluctuations, with patterns varying across different climate zones. Temperature had the greatest impact on the incidence of HFRS, with the maximum hysteresis effects being at 1 month (-19 ºC; relative risk [RR] 1.64, 95% CI 1.24-2.15) in the midtemperate zone, 0 months (28 ºC; RR 3.15, 95% CI 2.13-4.65) in the warm-temperate zone, and 0 months (4 ºC; RR 1.72, 95% CI 1.31-2.25) in the subtropical zone. Interactions were discovered between the average temperature, relative humidity, and precipitation in different temperature zones. Moreover, the influence of precipitation and relative humidity on the incidence of HFRS had different characteristics under different temperature layers. The hysteresis effect of meteorological factors did not end after an epidemic season, but gradually weakened in the following 1 or 2 seasons. CONCLUSIONS: Weather variability, especially low temperature, plays an important role in epidemics of HFRS in China. A long hysteresis effect indicates the necessity of continuous intervention following an HFRS epidemic. This finding can help public health departments guide the prevention and control of HFRS and develop strategies to cope with the impacts of climate change in specific regions.

The distinct spatiotemporal evolutionary landscape of HBV and HDV largely determines the unique epidemic features of HDV globally.

Chronic infection of hepatitis B virus (HBV) and hepatitis D virus (HDV) causes the most severe form of viral hepatitis. Due to the dependence on HBV, HDV was deemed to co-evolve and co-migrate with HBV. However, we previously found that the naturally occurred HDV/HBV combinations do not always reflect the most efficient virological adaptation (Wang et al., 2021). Moreover, regions with heavy HBV burden do not always correlate with high HDV prevalence (e.g., East Asia), and vice versa (e.g., Central Asia). Herein, we systematically elucidated the spatiotemporal evolutionary landscape of HDV to understand the unique epidemic features of HDV. We found that the MRCA of HDV was from South America around the late 13th century, was globally dispersed mainly via Central Asia, and evolved into eight genotypes from the 19th to 20th century. In contrast, the MRCA of HBV was from Europe ∼23.7 thousand years ago (Kya), globally dispersed mainly via Africa and East Asia, and evolved into eight genotypes ∼1100 years ago. When HDV stepped in, all present-day HBV genotypes had already formed and its global genotypic distribution had stayed stable geographically. Nevertheless, regionalized HDV adapted to local HBV genotypes and human lineages, contributing to the global geographical separation of HDV genotypes. Additionally, a sharp increase in HDV infections was observed after the 20th century. In conclusion, HDV exhibited a distinct spatiotemporal distribution path compared with HBV. This unique evolutionary relationship largely fostered the unique epidemic features we observe nowadays. Moreover, HDV infections may continue to ramp up globally, thus more efforts are urgently needed to combat this disease.

Strategies to foster community engagement for epidemic and pandemic preparedness and response in sub-Saharan Africa: a scoping review protocol.

INTRODUCTION: The surge of public health emergencies over the past decade has disproportionately affected sub-Saharan Africa. These include outbreaks of infectious diseases such as Ebola, Monkeypox and COVID-19. Experience has shown that community participation is key to the successful implementation of infection control activities. Despite the pivotal role community engagement plays in epidemic and pandemic preparedness and response activities, strategies to engage communities have been underexplored to date, particularly in sub-Sahara Africa. Furthermore, reviews conducted have not included evidence from the latest pandemic, COVID-19. This scoping review aims to address these gaps by documenting through available literature, the strategies for community engagement for epidemic and pandemic preparedness and response in sub-Sahara Africa. METHODS AND ANALYSIS: We will use the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews and the methodological framework for scoping reviews from Arksey and O'Malley to guide the review. Two reviewers will develop a systematic search strategy to identify articles published from January 2014 to date. We will retrieve peer-reviewed research published in the English language from databases including Embase, EBSCO-host, PubMed, Global Health, CINAHL, Google Scholar and Web of Science. Additionally, we will search for relevant grey literature from the websites of specific international organisations, public health institutes and Government Ministries of Health in African countries. After the removal of duplicates, the two reviewers will independently screen all titles, abstracts and full articles to establish the relevance of each study for inclusion in the review. We will extract data from the included articles using a data extraction tool and present the findings in tabular form with an accompanying narrative to aid comprehension. ETHICS AND DISSEMINATION: Ethical approval is not required for the conduct of scoping reviews. We plan to disseminate the findings from this review through publications in a peer-reviewed journal, presentations at conferences and meetings with policy-makers.