Since 2000, gains in access and use of vector control products (e.g., insecticide-treated bed nets and indoor residual spraying) contributed to substantial declines in malaria morbidity and mortality (32). Global gains in malaria control have plateaued in recent years, and disruptions due to the COVID-19 pandemic hindered country efforts to prioritize and implement interventions (2). Compared to nearly 60% in 2017, only 43% of the population in malaria endemic countries in sub-Saharan Africa used a bed net in 2020 (2). Compared to over 10% in 2010, only 5.3% of the population at-risk in the WHO Africa Region used residual spraying in 2020 (2). In contrast, the use of seasonal malaria chemoprevention among children has steadily increased since 2012 in the 13 Sahel countries in which it was implemented (2) (Supplementary Table 3). Although chemoprevention can be effective at reducing malaria morbidity and mortality during the high transmission season (33), it requires efficient microplanning and treatment adherence.
Against the backdrop of these challenges, resistance to ACTs has emerged as a major threat to malaria control efforts. Potential molecular markers of resistance have already been identified for drugs currently used for chemoprevention, including amodiaquine, lumefantrine, mefloquine, piperaquine, and artemisinins (4, 5, 26). The experience with chloroquine resistance is illustrative of the potential for the gains in malaria to be rolled back. Chloroquine resistance, caused by mutations in the PfCRT gene of the parasite, first emerged in South-East Asia and Latin America in the 1960s and in East Africa in the 1970s (34, 35) and quickly spread to other malaria endemic countries in sub-Saharan Africa (5, 34). In the 1980s, hospital studies from Nigeria, Congo, and the Democratic Republic of the Congo reported a two to three-fold increase in malaria deaths and admissions for severe malaria (6). Population-based studies from Senegal suggested malaria mortality among children increased nearly six-fold in areas that had previously achieved low levels of mortality using chloroquine for prophylaxis and treatment (6, 36). The molecular marker of artemisinin resistance Kelch 13 (Pfk13) was recently detected at low levels in Ghana, Rwanda, Uganda, and Tanzania. Resistant isolates to artemisinins and partner drugs could spread as rapidly, however, outpacing pharmaceutical development and reducing the effectiveness of current treatments (14). A modeling study of artemisinin resistance in all malaria endemic countries estimated $385 million USD in annual resistance-related productivity losses and an additional $32 million USD in annual medical expenditures (37).
Vaccines are a powerful tool against the emergence and spread of antimicrobial resistance (AMR). Vaccines prevent both drug-resistant and susceptible infections (14, 17, 18, 38). By reducing infections, vaccines reduce reliance on drug therapies and selective pressure driving resistance, thus averting significant health and economic burden (14). Recent studies by ARVac, a consortium of universities and organizations modeling the impact of vaccines on AMR, have quantified estimated health burden averted for several vaccines. A future rifampicin-resistant tuberculosis (RR-TB) could avert ~ 10% of resistant cases and ~ 7.3% of deaths from 2020 to 2035 in the 30 countries that account for 90% of global RR-TB incidence (39). Pneumococcal conjugate vaccines lead to absolute reductions in the proportions of pneumococci resistant to penicillin, sulfamethoxazole-trimethoprim, and third-generation cephalosporins by an estimated 7.3%, 16%, and 4.5%, respectively, on average across all regions during the 10-year period after their introduction (13). Under current coverage levels, rotavirus vaccines prevent an estimated 13.6 million episodes of antibiotic-treated illness among children under five years old in low- and middle-income countries, corresponding to a reduction of ~ 11.4% compared to a situation without a vaccine (18).
Vaccines benefit from a longstanding implementation infrastructure in Africa but only account for a fifth of total malaria R&D funding (2). Traditional vaccine development takes 1–10 years from pre-clinical trials to pilot implementation studies (40). It took over 30 years for RTS,S to gain regulatory approval after Phase III trials and enter pilot implementation studies. R21/Matrix-M showed high efficacy in a Phase IIb trial and has entered Phase III trials (41). If approved for implementation, R21 could drastically change the landscape of malaria vaccination as it may be more effective than RTS,S and uses a lower weight per dose (5µg compared to 25µg), which could lower the cost of large-scale manufacturing (22). Vaccine candidates that target different stages of the parasite life cycle (asexual blood-stage vaccines and transmission-blocking vaccines) are also in development (42). The PfRH5 vaccine and the PfS230 vaccine have both reached Phase II trials. A review by Duffy and Gorres (42) provides a comprehensive overview of malaria vaccine types, candidates, and development stages.
Our study, based on a mathematical model, indicates substantial malaria burden could be averted with a moderately effective vaccine regardless of waning time. Compared to a constant VE of 40% for four years dropping to 0% in year five (Scenario 1), the projected burden averted was greater when VE was higher right after vaccination (80%) and dropped 20 percentage points each year (Scenario 2) (Fig. 2). An initial spike followed by a gradual wane was observed in the seven-year follow-up study of RTS,S (24). This is consistent with VE trends of other vaccines and could be comparable to immunity after R21 vaccination; however, data from longitudinal studies of R21 are not yet available. Phase III trial results of RTS,S indicated approximately 40% efficacy at 48 months follow-up (25); however, it is difficult to quantify exactly how this will change after 48 months, which is why we included Scenario 1 and Scenario 3 (VE remains constant at 40% for the entire study). Cumulative cases averted in Scenario 3 surpassed those of Scenario 1 in 2025 and those of Scenario 2 in 2028 (Fig. 2), and the same trend was observed with resistant cases and deaths averted (Figs. 3 and 4). The increasing resistance scenario in which TFRs rose to 80% in 10 years depicts a worst-case scenario (Fig. 5). Given modern treatments and management for malaria, it is unlikely that TFRs would rise to such a figure. This situation highlights the importance of vaccines among tools to mitigate burden caused by drug resistance.
In combination with other control strategies (e.g., diagnostics, rapid access to treatment, and vector control products), an effective malaria vaccine could potentially reduce the disease burden even further than our projections. Our estimates of effect size are likely conservative for several reasons. First, we assumed vaccines would only be administered to one-year-olds entering the study each year, without a proposed catch-up campaign. Second, resistant cases averted in our study refer to detected and treated cases for which treatment fails. Many infections remain undetected, and individuals discontinue treatment over time. Third, we kept TFRs and CFRs constant over time when TFRs are likely to increase with increasing drug resistance, which would consequently increase CFRs without adequate control interventions. Fourth, we did not apply different incidence rates for sensitive versus resistant cases due to data availability. The proportion of cases that are resistant in a population is likely to increase over time without effective management due to longer illness duration and recrudescence. Similarly, we did not apply different CFRs for sensitive versus resistant cases. Mortality averted may be greater than our estimates project if CFRs for resistant cases are higher than for sensitive cases.
We used the most recent publicly available, country-specific data where possible; however, our analysis has some caveats. Vaccine efficacy varies between countries and within countries depending on several factors (e.g., endemicity level, vaccine coverage, and incomplete vaccination schedules). For each scenario, we assumed the same VE for all countries as country-specific estimates from trial data were only available for seven of the 42 countries in our study. We did not account for increased partial immunity after an infection or herd immunity. We used TFRs as a proxy for resistance, however, treatment failure may also be caused by poor compliance, inappropriate drug choice, or sub-therapeutic dosing (43). Many therapeutic efficacy studies from the Malaria Threats Map had sample sizes less than 30 (we only included studies with 30 or more samples), and studies from African countries had an average of only 75 samples per study. Imputed values for countries with missing treatment received and treatment failure rates may have biased results. We did not apply different incidence or mortality rates for sensitive versus resistant cases. Future modeling studies that examine these differences would further clarify the relationship between vaccines and health burden caused by drug resistance.
Capturing the complexities of malaria transmission at scale and over time is very difficult mainly because of spatial heterogeneity due to variable degrees of stochasticity between low- and high-transmission areas and treatment rate. In addition, drug resistance, vaccine efficacy, and mortality rate are highly dependent on drug type, stage of disease, and treatment duration, which can vary between and within countries. Dynamic models for smaller geographical areas, such as those compared by Penny et al. (44), provide more precise estimates; however, the application of such detailed models to evaluate public health impact for entire regions may not be practical due to their extensive data needs for parameterization. We determined the type of model, its specifications, and level of granularity given the large scope of this study (the entire WHO Africa Region). Accordingly, individual country results should be interpreted as aggregate estimates and with caution due to the many intra-country differences in endemicity, compliance with prevention strategies, and healthcare capacity.
While unknown factors on the evolution of drug resistance make it impossible to predict future health burden with exact precision, macro models using publicly available data produce useful aggregate projections at a macro scale. Our analysis aims to inform policymakers and vaccine developers on the urgency of an effective malaria vaccine. Development and implementation of an effective malaria vaccine should be accelerated to prevent the health and economic impacts of drug resistance, which will have a catastrophic impact when current therapies become ineffective (45).