Assessing the effectiveness of malaria interventions at the regional level in Ghana using a mathematical modelling application

Supporting malaria control with interfaced applications of mathematical models that enables investigating effectiveness of various interventions as well as their cost implications could be useful. Through their usage for planning, these applications may improve the prospects of attaining various set targets such as those of the National Strategic Plan policies for malaria control in Ghana. A malaria model was adapted and used for simulating the incidence of malaria in various regions of Ghana. The model and its application were developed by the Modelling and Simulation Hub Africa and calibrated using district level data in Ghana from 2012 to 2018. Average monthly rainfall at the zonal level was fitted to trigonometric functions for each ecological zone using least squares approach. These zonal functions were then used as forcing functions. Subsequently, various intervention packages were investigated to observe their impact on averting malaria incidence by 2030. Increased usage of bednets but not only coverage levels, predicted a significant proportion of cases of malaria averted in all regions. Whereas, improvements in the health system by way of health seeking, testing and treatment predicted a decline in incidence largely in all regions. With an increased coverage of SMC, to include higher age groups, a modest proportion of cases could be averted in populations of the Guinea savannah. Indoor residual spraying could also benefit populations of the Transitional forest and Coastal savannah as its impact is significant in averting incidence. Enhancing bednet usage to at least a doubling of the current usage levels and deployed in combination with various interventions across regions predicted significant reductions, in malaria incidence. Regions of the Transitional forest and Coastal savannah could also benefit from a drastic decline in incidence following a gradual introduction of indoor residual spraying on a sustained basis

The role of modelling and analytics in South African COVID-19 planning and budgeting

Background The South African COVID-19 Modelling Consortium (SACMC) was established in late March 2020 to support planning and budgeting for COVID-19 related healthcare in South Africa. We developed several tools in response to the needs of decision makers in the different stages of the epidemic, allowing the South African government to plan several months ahead. Methods Our tools included epidemic projection models, several cost and budget impact models, and online dashboards to help government and the public visualise our projections, track case development and forecast hospital admissions. Information on new variants, including Delta and Omicron, were incorporated in real time to allow the shifting of scarce resources when necessary. Results Given the rapidly changing nature of the outbreak globally and in South Africa, the model projections were updated regularly. The updates reflected 1) the changing policy priorities over the course of the epidemic; 2) the availability of new data from South African data systems; and 3) the evolving response to COVID-19 in South Africa, such as changes in lockdown levels and ensuing mobility and contact rates, testing and contact tracing strategies and hospitalisation criteria. Insights into population behaviour required updates by incorporating notions of behavioural heterogeneity and behavioural responses to observed changes in mortality. We incorporated these aspects into developing scenarios for the third wave and developed additional methodology that allowed us to forecast required inpatient capacity. Finally, real-time analyses of the most important characteristics of the Omicron variant first identified in South Africa in November 2021 allowed us to advise policymakers early in the fourth wave that a relatively lower admission rate was likely. Conclusion The SACMC’s models, developed rapidly in an emergency setting and regularly updated with local data, supported national and provincial government to plan several months ahead, expand hospital capacity when needed, allocate budgets and procure additional resources where possible. Across four waves of COVID-19 cases, the SACMC continued to serve the planning needs of the government, tracking waves and supporting the national vaccine rollout

Estimating the risk of declining funding for malaria in Ghana: the case for continued investment in the malaria response

Background Ghana has made impressive progress against malaria, decreasing mortality and morbidity by over 50% between 2005 and 2015. These gains have been facilitated in part, due to increased financial commitment from government and donors. Total resources for malaria increased from less than USD 25 million in 2006 to over USD 100 million in 2011. However, the country still faces a high burden of disease and is at risk of declining external financing due to its strong economic growth and the consequential donor requirements for increased government contributions. The resulting financial gap will need to be met domestically. The purpose of this study was to provide economic evidence of the potential risks of withdrawing financing to shape an advocacy strategy for resource mobilization. Methods A compartmental transmission model was developed to estimate the impact of a range of malaria interventions on the transmission of Plasmodium falciparum malaria between 2018 and 2030. The model projected scenarios of common interventions that allowed the attainment of elimination and those that predicted transmission if interventions were withheld. The outputs of this model were used to generate costs and economic benefits of each option. Results Elimination was predicted using the package of interventions outlined in the national strategy, particularly increased net usage and improved case management. Malaria elimination in Ghana is predicted to cost USD 961 million between 2020 and 2029. Compared to the baseline, elimination is estimated to prevent 85.5 million cases, save 4468 lives, and avert USD 2.2 billion in health system expenditures. The economic gain was estimated at USD 32 billion in reduced health system expenditure, increased household prosperity and productivity gains. Through malaria elimination, Ghana can expect to see a 32-fold return on their investment. Reducing interventions, predicted an additional 38.2 clinical cases, 2500 deaths and additional economic losses of USD 14.1 billion. Conclusions Malaria elimination provides robust epidemiological and economic benefits, however, sustained financing is need to accelerate the gains in Ghana. Although government financing has increased in the past decade, the amount is less than 25% of the total malaria financing. The evidence generated by this study can be used to develop a robust domestic strategy to overcome the financial barriers to achieving malaria elimination in Ghana

A retrospective study assessing the clinical outcomes and costs of acute hepatitis A in Cape Town, South Africa

Background While some evidence has been demonstrated the cost-effectiveness of routine hepatitis A vaccination in middle-income countries, the evidence is still limited in other settings including in South Africa. Given this, the evidence base around the cost of care for hepatitis A needs to be developed towards considerations of introducing hepatitis A vaccines in the national immunisation schedule and guidelines. Objectives To describe the severity, clinical outcomes, and cost of hepatitis A cases presenting to two tertiary healthcare centers in Cape Town, South Africa. Methods We conducted a retrospective folder review of patients presenting with hepatitis A at two tertiary level hospitals providing care for urban communities of metropolitan Cape Town, South Africa. Patients included in this folder review tested positive for hepatitis A immunoglobulin M between 1 January 2008 and 1 March 2018. Results In total, 239 folders of hepatitis A paediatric patients < 15 years old and 212 folders of hepatitis A adult patients $$\ge$$ ≥ 15 years old were included in the study. Before presenting for tertiary level care, more than half of patients presented for an initial consultation at either a community clinic or general physician. The mean length of hospital stay was 7.45 days for adult patients and 3.11 days for paediatric patients. Three adult patients in the study population died as a result of hepatitis A infection and 29 developed complicated hepatitis A. One paediatric patient in the study population died as a result of hepatitis A infection and 27 developed complicated hepatitis A, including 4 paediatric patients diagnosed with acute liver failure. The total cost per hepatitis A hospitalisation was $1935.41 for adult patients and$563.06 for paediatric patients, with overhead costs dictated by the length of stay being the largest cost driver. Conclusion More than 1 in every 10 hepatitis A cases (13.3%) included in this study developed complicated hepatitis A or resulted in death. Given the severity of clinical outcomes and high costs associated with hepatitis A hospitalisation, it is important to consider the introduction of hepatitis A immunisation in the public sector in South Africa to potentially avert future morbidity, mortality, and healthcare spending

Recommended reporting items for epidemic forecasting and prediction research : the EPIFORGE 2020 guidelines

Funding: MIDAS Coordination Center and the National Institutes of General Medical Sciences (NIGMS 1U24GM132013) for supporting travel to the face-to-face consensus meeting by members of the Working Group. NGR was supported by the National Institutes of General Medical Sciences (R35GM119582). Travel for SV was supported by the National Institutes of General Medical Sciences (1U24GM132013-01). BMA was supported by Bill & Melinda Gates through the Global Good Fund. RL was funded by a Royal Society Dorothy Hodgkin Fellowship.Background  The importance of infectious disease epidemic forecasting and prediction research is underscored by decades of communicable disease outbreaks, including COVID-19. Unlike other fields of medical research, such as clinical trials and systematic reviews, no reporting guidelines exist for reporting epidemic forecasting and prediction research despite their utility. We therefore developed the EPIFORGE checklist, a guideline for standardized reporting of epidemic forecasting research. Methods and findings  We developed this checklist using a best-practice process for development of reporting guidelines, involving a Delphi process and broad consultation with an international panel of infectious disease modelers and model end users. The objectives of these guidelines are to improve the consistency, reproducibility, comparability, and quality of epidemic forecasting reporting. The guidelines are not designed to advise scientists on how to perform epidemic forecasting and prediction research, but rather to serve as a standard for reporting critical methodological details of such studies. Conclusions  These guidelines have been submitted to the EQUATOR network, in addition to hosting by other dedicated webpages to facilitate feedback and journal endorsement.Publisher PDFNon peer reviewe

Accounting for regional transmission variability and the impact of malaria control interventions in Ghana : a population level mathematical modelling approach

CITATION: Awine, T. & Silal, S. P. 2020. Accounting for regional transmission variability and the impact of malaria control interventions in Ghana : a population level mathematical modelling approach. Malaria Journal, 19:423, doi:10.1186/s12936-020-03496-y.The original publication is available at https://malariajournal.biomedcentral.comBackground: This paper investigates the impact of malaria preventive interventions in Ghana and the prospects of achieving programme goals using mathematical models based on regionally diverse climatic zones of the country. Methods: Using data from the District Health Information Management System of the Ghana Health Service from 2008 to 2017, and historical intervention coverage levels, ordinary non-linear differential equations models were developed. These models incorporated transitions amongst various disease compartments for the three main ecological zones in Ghana. The Approximate Bayesian Computational sampling approach, with a distance based rejection criteria, was adopted for calibration. A leave-one-out approach was used to validate model parameters and the most sensitive parameters were evaluated using a multivariate regression analysis. The impact of insecticide-treated bed nets and their usage, and indoor residual spraying, as well as their protective efficacy on the incidence of malaria, was simulated at various levels of coverage and protective effectiveness in each ecological zone to investigate the prospects of achieving goals of the Ghana malaria control strategy for 2014–2020. Results: Increasing the coverage levels of both long-lasting insecticide-treated bed nets and indoor residual spraying activities, without a corresponding increase in their recommended utilization, does not impact highly on averting predicted incidence of malaria. Improving proper usage of long-lasting insecticide-treated bed nets could lead to substantial reductions in the predicted incidence of malaria. Similar results were obtained with indoor residual spraying across all ecological zones of Ghana. Conclusions: Projected goals set in the national strategic plan for malaria control 2014–2020, as well as World Health Organization targets for malaria pre-elimination by 2030, are only likely to be achieved if a substantial improvement in treated bed net usage is achieved, coupled with targeted deployment of indoor residual spraying with high community acceptability and efficacy.https://malariajournal.biomedcentral.com/articles/10.1186/s12936-020-03496-yPublisher's versio

Fig 8 -

Predictions for malaria incidence for various intervention packages, singly (a1-d1) for Community Health Worker (CHW), Health System Strengthening (HSS), Indoor Residual Spraying (IRS), and Insecticide Treated bednets (ITN) and in combination (a2-d2) for CHW/CHPS + ITN, HSS + ITN and ITN + IRS for the Ashanti (a1 and a2), Brong-Ahafo (b1 and b2), Eastern (c1 and c2) and Volta (d1 and d2) Regions respectively.</p

Factors associated with patterns of plural healthcare utilization among patients taking antiretroviral therapy in rural and urban South Africa: a cross-sectional study

Abstract Background In low-resource settings, patients’ use of multiple healthcare sources may complicate chronic care and clinical outcomes as antiretroviral therapy (ART) continues to expand. However, little is known regarding patterns, drivers and consequences of using multiple healthcare sources. We therefore investigated factors associated with patterns of plural healthcare usage among patients taking ART in diverse South African settings. Methods A cross-sectional study of patients taking ART was conducted in two rural and two urban sub-districts, involving 13 accredited facilities and 1266 participants selected through systematic random sampling. Structured questionnaires were used in interviews, and participant’s clinic records were reviewed. Data collected included household assets, healthcare access dimensions (availability, affordability and acceptability), healthcare utilization and pluralism, and laboratory-based outcomes. Multiple logistic regression models were fitted to identify predictors of healthcare pluralism and associations with treatment outcomes. Prior ethical approval and informed consent were obtained. Results Nineteen percent of respondents reported use of additional healthcare providers over and above their regular ART visits in the prior month. A further 15% of respondents reported additional expenditure on self-care (e.g. special foods). Access to health insurance (Adjusted odds ratio [aOR] 6.15) and disability grants (aOR 1.35) increased plural healthcare use. However, plural healthcare users were more likely to borrow money to finance healthcare (aOR 2.68), and incur catastrophic levels of healthcare expenditure (27%) than non-plural users (7%). Quality of care factors, such as perceived disrespect by staff (aOR 2.07) and lack of privacy (aOR 1.50) increased plural healthcare utilization. Plural healthcare utilization was associated with rural residence (aOR 1.97). Healthcare pluralism was not associated with missed visits or biological outcomes. Conclusion Increased plural healthcare utilization, inequitably distributed between rural and urban areas, is largely a function of higher socioeconomic status, better ability to finance healthcare and factors related to poor quality of care in ART clinics. Plural healthcare utilization may be an indication of patients’ dissatisfaction with perceived quality of ART care provided. Healthcare expenditure of a catastrophic nature remained a persistent complication. Plural healthcare utilization did not appear to influence clinical outcomes. However, there were potential negative impacts on the livelihoods of patients and their households.</p