Fiammetta Bozzani

Background: Antimicrobial resistance (AMR) poses a significant threat to global health and economic development. In Malawi, the economic costs associated with the treatment of AMR infections remain largely unknown which may hinder resource allocation and policy prioritization. Method: The study used a cross-sectional design and was conducted between September 2023 and January 2025 at three different hospital settings. Data were collected from inpatients with laboratory-confirmed urinary tract infection (UTI) or blood stream infection (BSI). Additional follow-up data were collected from patients for four weeks post discharge. We analyzed patient level data first using descriptive statistics and employed an instrumental variable 2-stage least squares regression to estimate drivers of AMR treatments costs. Results: A total of 610 patients participated in the study. Of these, 45% had AMR-associated resistant infections. Overall, E. coli (43%) followed by P. aeruginosa (22%), K. pneumoniae (14%), and S. aureus (10%) were the most common pathogens. UTI was marginally more common (51%) compared to BSI (49%). BSI had a higher average cost than UTI for patients with both susceptible and resistant infections. On average, a patient spent MK283,815.10 (US$163.71) ranging from zero to MK13,500,000 (US$7786.90). Patients with resistant infections incurred, on average, MK161,785 (US$93.32) more than patients with susceptible infections, largely driven by prolonged hospitalization among other factors. Overall, the direct medical observed costs averaged MK37,165.29 (US$21.44) while direct non-medical observed costs averaged MK61,908.71 (US$35.71). Productivity losses for the patient and guardian(s) were a major observed cost averaging MK160,322.80 (US$92.49). The regression results further showed that having a bank account as a proxy of wealth, non-farm business, longer travel duration, BSI, and K. pneumoniae as the causative pathogens were significantly associated with increased cost burden among the patients. Conclusions: AMR-associated infections impose substantial economic burden on patients and households. Further strengthening of AMR surveillance and stewardship are needed as critical elements of Malawi’s National Action Plan. However, measures should also be taken to mitigate the economic consequences related to AMR, especially for patients who bear the brunt of these costs for lack of financial protection in Malawi’s health system.

Background: Antimicrobial resistance (AMR) poses a significant threat to global health and economic development. In Malawi, the economic costs associated with AMR remain largely unknown which may hinder resource allocation and policy prioritization. Method: The study used instrumental variable 2-stage least squares regression to analyze patient level cost data at tertiary and secondary level facilities primarily collected from 610 patients with urinary tract infection (UTI) or blood stream infection (BSI) using a questionnaire. Results: Findings indicate that E. coli (43%) followed by K. pneumoniae (14%), and S. aureus (10%) were common pathogens overall. UTI was common (51%) compared to BSI (49%) yet BSI had a higher average cost than UTI for both susceptible and resistant patient categories. In terms of costs, a patient spent MK283,815.10 (US$163.71) on average as a result of AMR infection. The total cost reached as high as MK13,500,000 (US$7,786.90). Patients with a resistant infection incurred, on average MK161,785 (US$93.32) more than patients whose infection was susceptible, with the additional costs being driven by prolonged hospitalization among other factors. The direct medical costs averaged MK37,165.29 (US$21.44) while direct non-medical costs averaged MK61,908.71 (US$35.71). Productivity losses for the patient and guardian(s) were a major cost averaging MK160,322.80 (US$92.49). The regression results further showed that having a bank account as a proxy of wealth, non-farm business, longer travel duration, BSI, and K. pneumoniae as causing pathogens were significantly associated with increased cost burden among the patients. Conclusions: AMR imposes substantial economic burden on Malawi's health system, with most costs falling on patients. Further strengthening of AMR surveillance and stewardship are needed as critical elements of Malawi’s National Action Plan. However, measures should also be taken to mitigate the economic consequences related to AMR, especially for patients who bear the brunt of these costs for lack of financial protection in Malawi’s health system.

Background: Primary healthcare (PHC) is critical towards achieving Universal Health Coverage (UHC). In Ghana, PHC is organised at the district level and plays a key role in the country’s pursuit of UHC. However, many districts face challenges not only with limited resources but also with how effectively they are used. We examined how efficiently districts in Ghana use their health resources and what factors are associated with this efficiency. Methods: We used a two-step stochastic frontier analysis model using data from 181 districts. The output variable was a composite coverage index derived from eight PHC service indicators for 2021, primarily reflecting maternal and child health and infectious disease services. Input variables included district health expenditure for 2020/2021 and the number of health facilities and clinical staff in 2021. We then assessed the associations between efficiency scores generated by the model and health systems, socioeconomic and demographic factors, such as health facility type, insurance coverage, literacy level, Gini coefficient, poverty incidence, urbanisation and population density. Results: On average, districts operated at 87% efficiency, with scores ranging from 65% to 99%. Two factors were associated with the efficiency. First, districts with a higher proportion of PHC facilities tended to use resources more efficiently (coeff=0.151; 95% CI=0.041 to 0.261). Second, districts with greater income inequality were less efficient, measured by the Gini coefficient (coeff=−0.858; 95% CI=−1.146 to −0.252). Conclusion: Districts in Ghana have the potential to improve PHC outputs by about 13% on average by better use of existing resources and addressing determinants of efficiency. Findings suggest that districts with a higher proportion of PHC facilities and lower income inequality tend to be more efficient. These patterns highlight the value of strengthening PHC infrastructure and pursuing equity-focused policies as part of strategies to enhance efficiency in district health systems.

The end of the COVID-19 global health emergency presents an opportunity to reflect on actions needed to enhance the effectiveness of responses to any future shocks. We highlight critical areas requiring attention from researchers and research commissioners to enhance the identification and adoption of ‘good value’ interventions, and we discuss the complexities of evidence-informed decision-making across multiple sectors, the evolving role of modeling, and the need for improved stakeholder engagement and institutional coordination to effectively address interconnected health and policy challenges. We conclude the commentary by making a set of related recommendations to support intervention identification and implementation. Researchers, policymakers, and other key stakeholders should: renew efforts to step out of silos and to develop methods and frameworks that link and synthesize evidence from multiple sources and perspectives, to support planetary health goals and the ‘One Health’ concept; support more research into understanding the constraints to adopting interventions regarded as good value for money, to enhance evaluation methods ex ante and to better inform systems and stakeholders of the implementation requirements; and maintain an ongoing commitment to equitable research partnerships to ensure that evidence use is relevant for the target settings.

Tuberculosis infection prevention and control (TB IPC) measures are a cornerstone of policy, but measures are diverse and variably implemented. Limited attention has been paid to the health system environment which influences successful implementation of these measures. We used qualitative system dynamics and group-model-building methods 1) develop a qualitative causal map of the interlinked drivers of Mycobacterium tuberculosis (Mtb) transmission in South African primary health care facilities which in turn, helped us to 2) identify plausible IPC interventions to reduce risk of transmission. Two one-day participatory workshops were held in 2019 with policy- and decision-makers at national and provincial level, and patient advocates and health professionals at clinic and district level. Causal loop diagrams were generated by participants and combined by investigators. The research team reviewed diagrams to identify the drivers of nosocomial transmission of Mtb in primary health care facilities. Interventions proposed by participants were mapped onto diagrams to identify anticipated mechanisms of action and effect. Three systemic drivers were identified: 1) Mtb nosocomial transmission is driven by bottlenecks in patient flow at given times; 2) IPC implementation and clinic processes are anchored within a staff “culture of nominal compliance”; and 3) limited systems-learning at policy level inhibits effective clinic management and IPC implementation. Interventions prioritised by workshop participants included infrastructural, organisational, and behavioural strategies that target three areas: 1) improve air quality; 2) improve use of personal protective equipment; and 3) reduce the number of individuals in the clinic. In addition to core mechanisms, participants elaborated specific additional enablers that would help sustain implementation. Qualitative system dynamics modelling (SDM) methods allowed us to capture stakeholder views and potential solutions to address the problem of sub-optimal TB IPC implementation. The participatory elements of SDM facilitated problem-solving and inclusion of multiple factors frequently neglected when considering implementation.

Female genital schistosomiasis is a chronic gynaecological disease caused by the waterborne parasite Schistosoma (S.) haematobium. It affects an estimated 30–56 million girls and women globally, mostly in sub‐Saharan Africa where it is endemic, and negatively impacts their sexual and reproductive life. Recent studies found evidence of an association between female genital schistosomiasis and increased prevalence of HIV and cervical precancer lesions. Despite the large population at risk, the burden and impact of female genital schistosomiasis are scarcely documented, resulting in neglect and insufficient resource allocation. There is currently no standardised method for individual or population‐based female genital schistosomiasis screening and diagnosis which hinders accurate assessment of disease burden in endemic countries. To optimise financial allocations for female genital schistosomiasis screening, it is necessary to explore the cost‐effectiveness of different strategies by combining cost and impact estimates. Yet, no economic evaluation has explored the value for money of alternative screening methods. This paper describes a novel application of health decision analytical modelling to evaluate the cost‐effectiveness of different female genital schistosomiasis screening strategies across endemic settings. The model combines a decision tree for female genital schistosomiasis screening strategies, and a Markov model for the natural history of cervical cancer to estimate the cost per disability‐adjusted life‐years averted for different screening strategies, stratified by HIV status. It is a starting point for discussion and for supporting priority setting in a data‐sparse environment.

Female genital schistosomiasis (FGS) is a chronic gynaecological disease affecting girls and women in sub-Saharan Africa (SSA), caused by the parasite Schistosoma (S.) haematobium. FGS is associated with sexual dysfunction, reproductive tract morbidity and increased prevalence of HIV and cervical precancer lesions. Key peer-reviewed published literature. FGS screening and diagnosis require costly equipment and specialized training, seldom available in resource-limited settings. FGS surveillance is not included in wider schistosomiasis control strategies. The interplay of FGS with other SRH infections is not fully understood. Integration of FGS within sexual and reproductive health (SRH) control programmes needs to be explored. There are no standardized methods for individual or population-based FGS screening and diagnosis, hindering accurate disease burden estimates and targeted resource allocation. Treatment recommendations rely on public health guidelines, without rigorous clinical evidence on efficacy. Integrating FGS screening with SRH programmes offers an opportunity to reach at-risk women with limited access to healthcare services. Home-based self-sampling coupled with handheld colposcopes operated by primary healthcare workers show promise for FGS diagnosis and surveillance at scale. There is growing interest in decentralizing strategies for FGS screening and diagnosis. The accurate predictions on the ‘cost-effectiveness’ of these approaches will determine their affordability and feasibility within the overburdened health systems in SSA. Clinical trials are needed to optimize FGS treatment. Longitudinal studies can expand on the epidemiological knowledge on co-morbidities and integration within other SRH interventions.

In clinical settings where airborne pathogens, such as Mycobacterium tuberculosis, are prevalent, they constitute an important threat to health workers and people accessing healthcare. We report key insights from a 3-year project conducted in primary healthcare clinics in South Africa, alongside other recent tuberculosis infection prevention and control (TB-IPC) research. We discuss the fragmentation of TB-IPC policies and budgets; the characteristics of individuals attending clinics with prevalent pulmonary tuberculosis; clinic congestion and patient flow; clinic design and natural ventilation; and the facility-level determinants of the implementation (or not) of TB-IPC interventions. We present modeling studies that describe the contribution of M. tuberculosis transmission in clinics to the community tuberculosis burden and economic evaluations showing that TB-IPC interventions are highly cost-effective. We argue for a set of changes to TB-IPC, including better coordination of policymaking, clinic decongestion, changes to clinic design and building regulations, and budgeting for enablers to sustain implementation of TB-IPC interventions. Additional research is needed to find the most effective means of improving the implementation of TB-IPC interventions; to develop approaches to screening for prevalent pulmonary tuberculosis that do not rely on symptoms; and to identify groups of patients that can be seen in clinic less frequently.

Background The HIV epidemic remains a major public health problem. Critical to transmission control are HIV prevention strategies with new interventions continuing to be developed. Mathematical models are important for understanding the potential impact of these interventions and supporting policy decisions. This systematic review aims to answer the following question: when a new HIV prevention intervention is being considered or designed, what information regarding it is necessary to include in a compartmental model to provide useful insights to policy makers? The primary objective of this review is therefore to assess suitability of current compartmental HIV prevention models for informing policy development. Methods Articles published in EMBASE, Medline, Econlit, and Global Health were screened. Included studies were identified using permutations of (i) HIV, (ii) pre-exposure prophylaxis (PrEP), circumcision (both voluntary male circumcision [VMMC] and early-infant male circumcision [EIMC]), and vaccination, and (iii) modelling. Data extraction focused on study design, model structure, and intervention incorporation into models. Article quality was assessed using the TRACE (TRAnsparent and Comprehensive Ecological modelling documentation) criteria for mathematical models. Results Of 837 articles screened, 48 articles were included in the review, with 32 unique mathematical models identified. The substantial majority of studies included PrEP (83%), whilst fewer modelled circumcision (54%), and only a few focussed on vaccination (10%). Data evaluation, implementation verification, and model output corroboration were identified as areas of poorer model quality. Parameters commonly included in the mathematical models were intervention uptake and effectiveness, with additional intervention-specific common parameters identified. We identified key modelling gaps; critically, models insufficiently incorporate multiple interventions acting simultaneously. Additionally, population subgroups were generally poorly represented—with future models requiring improved incorporation of ethnicity and sexual risk group stratification—and many models contained inappropriate data in parameterisation which will affect output accuracy. Conclusions This review identified gaps in compartmental models to date and suggests areas of improvement for models focusing on new prevention interventions. Resolution of such gaps within future models will ensure greater robustness and transparency, and enable more accurate assessment of the impact that new interventions may have, thereby providing more meaningful guidance to policy makers.

Introduction: Nosocomial Mycobacterium tuberculosis (Mtb) transmission substantially impacts health workers, patients and communities. Guidelines for tuberculosis infection prevention and control (TB IPC) exist but implementation in many settings remains suboptimal. Evidence is needed on cost-effective investments to prevent Mtb transmission that are feasible in routine clinic environments. Methods: A set of TB IPC interventions was codesigned with local stakeholders using system dynamics modelling techniques that addressed both core activities and enabling actions to support implementation. An economic evaluation of these interventions was conducted at two clinics in KwaZulu-Natal, employing agent-based models of Mtb transmission within the clinics and in their catchment populations. Intervention costs included the costs of the enablers (eg, strengthened supervision, community sensitisation) identified by stakeholders to ensure uptake and adherence. Results: All intervention scenarios modelled, inclusive of the relevant enablers, cost less than US$200 per disability-adjusted life-year (DALY) averted and were very cost-effective in comparison to South Africa’s opportunity cost-based threshold (US$3200 per DALY averted). Two interventions, building modifications to improve ventilation and maximising use of the existing Central Chronic Medicines Dispensing and Distribution system to reduce the number of clinic attendees, were found to be cost saving over the 10-year model time horizon. Incremental cost-effectiveness ratios were sensitive to assumptions on baseline clinic ventilation rates, the prevalence of infectious TB in clinic attendees and future HIV incidence but remained highly cost-effective under all uncertainty analysis scenarios. Conclusion: TB IPC interventions in clinics, including the enabling actions to ensure their feasibility, afford very good value for money and should be prioritised for implementation within the South African health system.