Malaria: a parasite, a mosquito, and a number called R0

Topic: malaria: the parasite, the mosquito, R0, and the first vaccines · Since 1990 · Grounded citations only · Published 2026-08-22

Start here: what malaria is

Malaria is caused by single-celled parasites of the genus Plasmodium, carried between people by female Anopheles mosquitoes. It is not contagious in the ordinary sense — you cannot catch it from another person. The parasite needs the mosquito, and the mosquito needs to bite twice: once to pick the parasite up, once to put it down.

That two-host requirement is the disease's central weakness, and the reason a mathematical model sits at the heart of this review rather than at the end of it.

What it does to a person. An infected mosquito injects sporozoites, which travel to the liver and multiply silently inside hepatocytes — "the silent path to thousands of merozoites" [1]. Nothing is felt during this stage. Then the liver cells burst and release merozoites into the blood, where they invade red cells, consume them, multiply, and burst out again on a roughly synchronised cycle. That synchronised rupture is the classic cyclical fever. Some parasites differentiate into gametocytes, the sexual stage that a biting mosquito can pick up, closing the loop [2] [3].

Which species. Five Plasmodium species infect humans, and two dominate. P. falciparum causes almost all severe disease and nearly all deaths, largely because infected red cells stick to blood-vessel walls via the variant surface protein PfEMP1, obstructing microcirculation — the mechanism behind cerebral malaria [4] [5]. P. vivax is more geographically widespread than long assumed [6] and has a feature falciparum lacks: dormant liver forms called hypnozoites that reactivate weeks or months later, causing relapses from a single bite [7] [8] [9]. Vivax is not the benign disease it was once called; it is associated with severe and fatal malaria too [10] [11].

Scale. Malaria remains one of the largest infectious-disease burdens on earth, concentrated overwhelmingly in sub-Saharan Africa and falling most heavily on young children [12] [13] [14]. Geostatistical mapping of P. falciparum endemicity has repeatedly reset the picture of where transmission actually is and how intense [15] [16].

Why it is in the news. Two things at once, pulling in opposite directions.

1. The first malaria vaccines are being deployed. After decades in which no vaccine against any human parasite existed, two now do — RTS,S/AS01 and R21/Matrix-M, both targeting the circumsporozoite protein on the sporozoite [17] [18]. 2. Artemisinin partial resistance is spreading, and has reached Africa. The drug class that underpins essentially all frontline treatment is losing potency, first on the Thai–Cambodian border [19] [20], then across Southeast Asia [21], and now with independently emerged resistant parasites documented in Africa [22] [23].

And the connection to sickle cell disease. Malaria is the strongest selective pressure known to have acted on the human genome, and the sickle-cell allele is its most famous fingerprint. Carrying one copy protects against malaria; carrying two causes sickle cell disease. That trade-off — balancing selection, the "malaria hypothesis" — is why a lethal allele persists at high frequency across malarious Africa, confirmed geographically by comparing HbS allele-frequency maps against pre-intervention malaria endemicity [24] [25]. The sickle review models that equilibrium; this review is the other half of the story: the parasite doing the selecting.

Three pillars follow — measurements, medicines and prevention, and progress — with the Ross–Macdonald model in between.

Pillar 1: measurements and diagnosis

Finding the parasite

Microscopy remains the reference standard: a drop of blood, stained and read under a light microscope, showing parasites inside red cells. It gives species identification and, crucially, a parasitaemia — the percentage of red cells infected, which grades severity and tracks response to treatment. Its weakness is operational rather than scientific: it needs a trained microscopist, a working microscope and electricity, and it is "clearly inadequate in many health care settings" [26] [27].

Rapid diagnostic tests (RDTs) solved the access problem. A lateral-flow strip detects a parasite antigen from a finger-prick in about fifteen minutes with no equipment. The dominant target is HRP2, histidine-rich protein 2, produced by P. falciparum. RDTs transformed case management by making a parasitological diagnosis possible where microscopy was not, and trials compared them directly against microscopy for guiding outpatient treatment of febrile illness [28] [26].

Two failure modes matter, and both are grounded. HRP2 is genetically variable, and that diversity affects test performance across parasite populations [29]. Worse, parasites that have deleted the pfhrp2 and pfhrp3 genes are invisible to HRP2-based tests — a large proportion of isolates in the Amazon region of Peru lack these genes, with direct implications for RDT-based diagnosis [30]. A diagnostic that selects for parasites which evade it is a control problem, not just a laboratory one.

And a large reservoir is asymptomatic. Low-density, often sub-microscopic infections are common in low-transmission settings and sustain onward transmission without anyone feeling ill — "the silent threat" [31] [32]. As programmes push toward elimination, the diagnostic requirement shifts from "is this fever malaria?" to "who is carrying parasites at all?", which is a far more sensitive test [33] [34] [35].

Recognising severe disease

Severe falciparum malaria is a distinct clinical emergency — impaired consciousness, respiratory distress, severe anaemia, acidosis, hypoglycaemia, and high parasitaemia — and it is what kills [36] [37]. Cerebral malaria has a characteristic neuropathology in African children [5]. The distinction between uncomplicated and severe disease determines the entire treatment pathway, because it changes the drug and the route.

Centerpiece: the Ross–Macdonald model

Malaria control has a quantitative theory, and it is older than most of the drugs.

Because transmission requires a mosquito to bite an infectious human and later bite a susceptible one, the parasite's reproductive success depends on mosquito behaviour and mosquito lifespan far more than on anything about the parasite. Ronald Ross and George Macdonald formalised this; a systematic historical review shows the model was built by several contributors over some seventy years, and that "all the basic elements of the theory had fallen into place by the end of the Global Malaria Eradication Programme ... with the concept of vectorial capacity, methods for measuring key components of transmission by mosquitoes, and a quantitative theory of vector control" [38] [39].

The vectorial capacity V is the number of infectious bites that will eventually arise from all the mosquitoes biting one infectious human on one day:

V = m · a² · e^(−μn) / μ

and the basic reproduction number — secondary human cases from one infectious human in a fully susceptible population — follows by multiplying by the transmission efficiencies and the human infectious period:

R₀ = V · b · c / r

with m mosquitoes per human, a the human biting rate per mosquito per day, b and c the transmission probabilities mosquito→human and human→mosquito, μ the mosquito daily death rate, n the extrinsic incubation period (the days the parasite needs to develop inside the mosquito), and r the human recovery rate.

Read the exponents; they are the whole argument.

That asymmetry is not a curiosity — it is the reason vector control looks the way it does. As a re-analysis of the theory puts it, the historical choice of intervention "has been largely guided by a parameter sensitivity analysis of George Macdonald's theory of vectorial capacity that suggested prioritizing methods that kill adult mosquitoes" [40].

Grounding and parameters. The model form, the vectorial-capacity decomposition, and the adult-mortality priority are all grounded above [38] [40]. The parameter values are illustrative and flagged — every one of them, plus the coupling from intervention coverage to the parameter it changes (the adult-killing curve assumes coverage proportionally shortens mosquito lifespan, a teaching simplification, not a fitted relationship). The one external constraint the figure is required to satisfy is empirical: R₀ was estimated for 121 African populations and the estimates "range from around one to more than 3,000" [41], and the script asserts its baseline falls inside that range.

0 20 40 60 80 intervention coverage, % 1 0 − 1 1 0 0 1 0 1 1 0 2 1 0 3 basic reproduction number R0 (log scale) R0 = 1: the elimination threshold reduce mosquito density (R0 ~ 1-C) reduce biting only (R0 ~ (1-C)^2) kill adult mosquitoes (ITN / IRS) killing adult mosquitoes crosses R0 = 1 at 79% coverage; cutting bites alone needs 94%; cutting mosquito numbers alone needs 99.7% Ross-Macdonald: why vector control targets mosquito survival
Computed Ross-Macdonald reproduction number R0 = m*a^2*exp(-mu*n)/mu * b*c/r against intervention coverage, on a log scale, from an illustrative baseline of R0 = 300 - inside the published range of 1 to more than 3000 estimated across 121 African populations (Smith et al., PLoS Biol 2007 [W2120463581]), which the script asserts. Three control strategies are compared. Reducing mosquito DENSITY scales R0 linearly and reaches the R0 = 1 elimination threshold only at 99.7% coverage. Reducing BITING alone scales it quadratically, reaching the threshold at 94%. KILLING ADULT MOSQUITOES reaches it at 79%, because mosquito mortality enters twice - through the lifespan term 1/mu and through the exponential probability exp(-mu*n) of surviving the extrinsic incubation period. That ordering is the quantitative reason Macdonald's sensitivity analysis prioritised adult-killing methods such as insecticide-treated nets and indoor residual spraying (Brady et al. 2016 [W2271242314]; model form from Smith et al., PLoS Pathog 2012 [W2066245205]). All parameter values and the coverage-to-parameter couplings are ILLUSTRATIVE teaching choices, not fitted estimates.

What the model explains. Three things.

First, why insecticide-treated nets work better than they "should." A net is not merely a barrier. Treated with insecticide it also kills the mosquito that lands on it — so it acts on both a and μ simultaneously, and the μ term is the powerful one. Community-wide effects follow: nets protect people who do not sleep under them, because the mosquito population itself is being culled [42] [43].

Second, why R₀ varies so enormously between places, and why one control package cannot fit all. With estimates spanning three orders of magnitude, "malaria control presents variable challenges across its transmission spectrum"; where R₀ is highest, control "will require multiple, integrated methods that target those who are bitten most" [41]. Heterogeneous biting — a minority of people receiving most bites — is itself a first-order term [41] [44] [45].

Third, why elimination is harder than control. Getting R₀ from 300 to 3 is easy on a log scale and eliminates almost all cases; getting it from 3 to below 1 is where the last interventions have to work, and that is exactly where the sensitivity analysis needs revisiting — adult-killing methods alone leave "effective coverage gaps" from physiological and behavioural resistance, so other methods are needed to fill them [40] [46].

Limits, honestly. The Ross–Macdonald model assumes a homogeneous, well-mixed population, constant parameters, and no acquired immunity — all false. Formal sensitivity analyses of richer models identify which parameters actually dominate in practice [47], mosquito ecology and life cycle add structure the classical model omits [48] [49], temperature constrains transmission geographically [50], and R₀ estimated from serology gives yet another answer [51]. The model earns its place not by being accurate but by being right about what matters.

Pillar 2: medicines and prevention

Treatment: ACTs, and the resistance closing in

Artemisinin derivatives kill parasites faster than any other antimalarial class. Because rapid monotherapy invites resistance, they are given as artemisinin-based combination therapy (ACT) — a fast-acting artemisinin paired with a slower, longer-lasting partner drug that clears the residuum. ACTs are the recommended first-line treatment for falciparum malaria in every endemic country [20]. Supply was itself a scientific problem, solved by semi-synthetic production of artemisinin [52].

For severe malaria the answer is not oral and not quinine. A randomised trial of artesunate versus quinine in severe falciparum malaria established intravenous artesunate as superior [53], displacing a drug that had been in use for centuries [54].

The resistance story is the one to follow, and it is well documented. Reduced susceptibility appeared in western Cambodia [19], and was characterised as markedly prolonged parasite clearance: median clearance times of 84 hours in Pailin versus 48 hours in northwestern Thailand [20]. A multi-site study of 1,241 patients across 15 sites in 10 countries then mapped its extent, finding parasite clearance half-lives from 1.9 hours in the Democratic Republic of Congo to 7.0 hours at the Thailand–Cambodia border, with slow clearance strongly associated with mutations in the kelch13 propeller region [21]. That gave the field a molecular marker it could survey with [55] [56] [57], and the marker is what detected independent emergence in Africa, including clonal expansion of a kelch13 R561H mutant [22] [23] [58]. Antimalarial resistance is an old pattern repeating with a new drug class [59].

Prevention: vector control, and its own resistance problem

Insecticide-treated nets are the most prominent large-scale preventive measure in highly endemic areas, and the Cochrane review assessed their impact on mortality, illness, parasitaemia and anaemia [43]; community-wide effects on child mortality were demonstrated in western Kenya [42], and combined ACT-plus-net scale-up produced measurable burden reduction in Zanzibar [60] and falling transmission in Kilifi [61]. Net scale-up has even been associated with historical population decline in Anopheles gambiae [62]. Indoor residual spraying is the other adult-killing pillar [63].

Both are eroding, in two distinct ways.

Which vectors matter, and where, is itself mapped [68] [69] [70].

The vaccines

Both licensed vaccines target the same thing: the circumsporozoite protein (CSP) coating the sporozoite during the brief window between the mosquito's bite and the parasite reaching the liver. Block it there and infection never becomes blood-stage disease. That is a narrow window and a high bar, which is why the field took so long — the approach traces back to a preliminary evaluation of a recombinant CSP vaccine in 1997 [71], supported by the observation that sporozoite inoculation can itself confer protection [72].

RTS,S/AS01 was the first to succeed. Efficacy against clinical and severe malaria was shown in young African children [73], then in a large phase 3 programme reporting first results [74], results in infants [75], and final efficacy and safety with and without a booster dose [17]. Its benchmark, as later trials describe it, was "56% efficacy over 12 months in African children" [76]. Seasonal delivery combined with seasonal chemoprevention was then tested as a way to get more out of it [77].

R21/Matrix-M is the second, built on the same CSP target but with a higher proportion of CSP in the particle and the saponin adjuvant Matrix-M [78]. A phase 2b trial in Nanoro, Burkina Faso, gave three doses before the malaria season with a fourth a year later to children aged 5–17 months [76], with efficacy and immunogenicity sustained at two years' follow-up [79], followed by a multicentre, double-blind, randomised phase 3 in African children [18]. Modelling has estimated its public-health impact and cost-effectiveness at scale [80].

Both are partial vaccines. Neither is a substitute for nets or treatment; they are an added layer.

Why some people are protected without any of this

Malaria's selective pressure has left several protective variants in human populations, and the red cell is where almost all of them act [81] [82]. Sickle cell trait (HbAS) is the canonical case [24] [25], and G6PD deficiency is another, common enough across malaria-endemic countries to have been mapped geostatistically [83].

The mechanism connects directly to the sickle cell disease review. Rather than the parasite simply failing to grow, P. falciparum developed similarly in normal red cells and in sickle-trait, β- and α-thalassaemia-trait cells — but membrane-bound hemichromes, autologous IgG, complement C3c fragments, aggregated band 3 and phagocytosis by human monocytes were markedly higher in rings developing in the mutant cells. Enhanced, largely complement-mediated phagocytosis of ring-parasitised mutant erythrocytes is proposed as the common mechanism explaining protection across several of these red-cell variants [84] [85].

Pillar 3: progress

Vaccine scale-up is the immediate story, with two licensed products, seasonal-delivery strategies, and impact modelling to guide where doses go first [17] [18] [77] [80]. Whole-sporozoite approaches are a separate line with their own randomised evidence [86].

Monoclonal antibodies skip vaccination entirely and deliver the anti-CSP antibody directly — subcutaneous administration of a monoclonal antibody to prevent malaria has been tested in the field, offering a potential seasonal-protection tool for children [87].

Gene drives attack the vector's genome rather than the parasite. A CRISPR–Cas9 gene drive targeting doublesex caused complete population suppression in caged Anopheles gambiae [88] — a laboratory result whose ecological and governance questions are as large as its technical promise. Manipulating the mosquito's midgut microbiota is a gentler variant of the same idea [89].

Resistance management is the defensive half of the agenda: molecular surveillance for kelch13 [55] [22], next-generation insecticides and synergist nets [66] [65], and the recognition that residual transmission needs tools that neither nets nor spraying provide [46] [67].

And elimination remains the framing goal, with research agendas set out explicitly [90] [91], strategies shifting as epidemiology changes at low transmission [92] [93], hotspot targeting and human-mobility data to find where transmission actually persists [44] [45], and regional programmes facing their own constraints [94] [14]. Climate is a live variable in where transmission is possible at all [50] [95] [96].

Dig deeper in lmmol

  • Sickle cell disease — the other half of the balanced-polymorphism story. Malaria is the selective pressure that maintains the sickle allele; that review models the equilibrium, this one describes the parasite doing the selecting [24] [84].
  • The health reviews index collects the rest of the series.
  • Haemoglobin subunit beta — the β-globin chain whose single substitution produces sickle trait, the best-characterised malaria-protective variant in the human genome [25] [84].
  • Haemoglobin subunit alpha — α-thalassaemia trait is a second red-cell variant enriched in malarious regions and examined in the same phagocytosis work [84].
  • Pyrimethamine and atovaquone — two antimalarials whose resistance histories illustrate the pattern now unfolding with artemisinin [59].
  • For entities without a linked static page here, use the graph index, all diseases, or all proteins rather than guessing an entity URL.

Key papers

  1. W1983531823: The silent path to thousands of merozoites: the Plasmodium liver stage (cited 518×)
  2. W2164365774: Discovery of Gene Function by Expression Profiling of the Malaria Parasite Life Cycle (cited 1,336×)
  3. W2156022009: A proteomic view of the Plasmodium falciparum life cycle (cited 1,307×)
  4. W2072975902: Plasmodium falciparum Erythrocyte Membrane Protein 1 Diversity in Seven Genomes – Divide and Conquer (cited 408×)
  5. W2152846661: The Neuropathology of Fatal Cerebral Malaria in Malawian Children (cited 300×)
  6. W2137862593: A Long Neglected World Malaria Map: Plasmodium vivax Endemicity in 2010 (cited 567×)
  7. W2159276995: Determinants of relapse periodicity in Plasmodium vivax malaria (cited 719×)
  8. W1924088672: Strategies for Understanding and Reducing the Plasmodium vivax and Plasmodium ovale Hypnozoite Reservoir in Papua New Guinean Children: A Randomised Placebo-Controlled Trial and Mathematical Model (cited 297×)
  9. W2151383900: Comparative genomics of the neglected human malaria parasite Plasmodium vivax (cited 865×)
  10. W2152507925: Multidrug-Resistant Plasmodium vivax Associated with Severe and Fatal Malaria: A Prospective Study in Papua, Indonesia (cited 621×)
  11. W2085946003: Plasmodium vivax and Mixed Infections Are Associated with Severe Malaria in Children: A Prospective Cohort Study from Papua New Guinea (cited 482×)
  12. W3092849554: Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019 (cited 19,729×)
  13. W1871026043: CONQUERING THE INTOLERABLE BURDEN OF MALARIA: WHAT’S NEW, WHAT’S NEEDED: A SUMMARY (cited 674×)
  14. W4395073970: Current Status of Malaria Control and Elimination in Africa: Epidemiology, Diagnosis, Treatment, Progress and Challenges (cited 143×)
  15. W2144207524: A new world malaria map: Plasmodium falciparum endemicity in 2010 (cited 1,176×)
  16. W4241516881: A World Malaria Map: Plasmodium falciparum Endemicity in 2007 (cited 511×)
  17. W4254848468: Efficacy and safety of RTS,S/AS01 malaria vaccine with or without a booster dose in infants and children in Africa: final results of a phase 3, individually randomised, controlled trial (cited 1,506×)
  18. W4391671314: Safety and efficacy of malaria vaccine candidate R21/Matrix-M in African children: a multicentre, double-blind, randomised, phase 3 trial (cited 379×)
  19. W2040713555: Evidence of Artemisinin-Resistant Malaria in Western Cambodia (cited 1,833×)
  20. W2161311583: Artemisinin Resistance in Plasmodium falciparum Malaria (cited 3,472×)
  21. W2171102256: Spread of Artemisinin Resistance in Plasmodium falciparum Malaria (cited 2,280×)
  22. W3200040377: Evidence of Artemisinin-Resistant Malaria in Africa (cited 960×)
  23. W3046809066: Emergence and clonal expansion of in vitro artemisinin-resistant Plasmodium falciparum kelch13 R561H mutant parasites in Rwanda (cited 915×)
  24. W2128855640: Global distribution of the sickle cell gene and geographical confirmation of the malaria hypothesis (cited 618×)
  25. W2026796607: Sickle Hemoglobin (Hb S) Allele and Sickle Cell Disease: A HuGE Review (cited 537×)
  26. W2143917555: Update on Rapid Diagnostic Testing for Malaria (cited 510×)
  27. W1980712697: Malaria Diagnosis: A Brief Review (cited 605×)
  28. W1984557452: Rapid diagnostic tests compared with malaria microscopy for guiding outpatient treatment of febrile illness in Tanzania: randomised trial (cited 439×)
  29. W2036927864: Genetic Diversity ofPlasmodium falciparumHistidine‐Rich Protein 2 (PfHRP2) and Its Effect on the Performance of PfHRP2‐Based Rapid Diagnostic Tests (cited 348×)
  30. W2010328983: A Large Proportion of P. falciparum Isolates in the Amazon Region of Peru Lack pfhrp2 and pfhrp3: Implications for Malaria Rapid Diagnostic Tests (cited 577×)
  31. W2050811145: The silent threat: asymptomatic parasitemia and malaria transmission (cited 643×)
  32. W2147272002: A large proportion of asymptomatic Plasmodium infections with low and sub-microscopic parasite densities in the low transmission setting of Temotu Province, Solomon Islands: challenges for malaria diagnostics in an elimination setting (cited 306×)
  33. W2185132500: Comparison of diagnostics for the detection of asymptomatic Plasmodium falciparum infections to inform control and elimination strategies (cited 271×)
  34. W2113932936: Targeting Asymptomatic Malaria Infections: Active Surveillance in Control and Elimination (cited 358×)
  35. W2793593056: A Research Agenda for Malaria Eradication: Diagnoses and Diagnostics (cited 256×)
  36. W1622422817: Clinical review: Severe malaria. (cited 536×)
  37. W2135802236: CLINICAL ASPECTS OF UNCOMPLICATED AND SEVERE MALARIA (cited 312×)
  38. W2066245205: Ross, Macdonald, and a Theory for the Dynamics and Control of Mosquito-Transmitted Pathogens (cited 651×)
  39. W2165151302: Mathematical models of malaria - a review (cited 405×)
  40. W2271242314: Vectorial capacity and vector control: reconsidering sensitivity to parameters for malaria elimination (cited 259×)
  41. W2120463581: Revisiting the Basic Reproductive Number for Malaria and Its Implications for Malaria Control (cited 487×)
  42. W2154246179: COMMUNITY-WIDE EFFECTS OF PERMETHRIN-TREATED BED NETS ON CHILD MORTALITY AND MALARIA MORBIDITY IN WESTERN KENYA (cited 652×)
  43. W2094077008: Insecticide-treated bed nets and curtains for preventing malaria (cited 1,724×)
  44. W2138055306: Hitting Hotspots: Spatial Targeting of Malaria for Control and Elimination (cited 597×)
  45. W2319284762: Identifying Malaria Transmission Foci for Elimination Using Human Mobility Data (cited 176×)
  46. W2152400766: Characterizing, controlling and eliminating residual malaria transmission (cited 544×)
  47. W2102798763: Determining Important Parameters in the Spread of Malaria Through the Sensitivity Analysis of a Mathematical Model (cited 1,836×)
  48. W2136547339: A malaria transmission-directed model of mosquito life cycle and ecology (cited 209×)
  49. W2143138689: Statics and dynamics of malaria infection in Anopheles mosquitoes. (cited 518×)
  50. W2092203201: Modelling the global constraints of temperature on transmission of Plasmodium falciparum and P. vivax (cited 226×)
  51. W1991762787: Estimation of the Basic Reproduction Number for Infectious Diseases from Age-Stratified Serological Survey Data (cited 184×)
  52. W1990226486: High-level semi-synthetic production of the potent antimalarial artemisinin (cited 2,104×)
  53. W1673362020: Artesunate versus quinine for treatment of severe falciparum malaria: a randomised trial (cited 1,073×)
  54. W2135874703: Quinine, an old anti-malarial drug in a modern world: role in the treatment of malaria (cited 991×)
  55. W2124634096: A molecular marker of artemisinin-resistant Plasmodium falciparum malaria (cited 2,190×)
  56. W1993347313: K13-propeller mutations confer artemisinin resistance in Plasmodium falciparum clinical isolates (cited 751×)
  57. W1969571661: Genetic architecture of artemisinin-resistant Plasmodium falciparum (cited 654×)
  58. W2135926190: Emergence of artemisinin-resistant malaria on the western border of Thailand: a longitudinal study (cited 938×)
  59. W2064855181: Antimalarial drug resistance (cited 1,173×)
  60. W2036368368: Impact of Artemisinin-Based Combination Therapy and Insecticide-Treated Nets on Malaria Burden in Zanzibar (cited 665×)
  61. W2168330471: Effect of a fall in malaria transmission on morbidity and mortality in Kilifi, Kenya (cited 449×)
  62. W2119684348: Anopheles gambiae: historical population decline associated with regional distribution of insecticide-treated bed nets in western Nyanza Province, Kenya (cited 542×)
  63. W2999516102: The importance of vector control for the control and elimination of vector-borne diseases (cited 927×)
  64. W2133315237: Reduced Efficacy of Insecticide-treated Nets and Indoor Residual Spraying for Malaria Control in Pyrethroid Resistance Area, Benin (cited 573×)
  65. W2166537326: Role of cytochrome P450s in insecticide resistance: impact on the control of mosquito-borne diseases and use of insecticides on Earth (cited 423×)
  66. W2796879453: Effectiveness of a long-lasting piperonyl butoxide-treated insecticidal net and indoor residual spray interventions, separately and together, against malaria transmitted by pyrethroid-resistant mosquitoes: a cluster, randomised controlled, two-by-two factorial design trial (cited 522×)
  67. W2103610338: Increased proportions of outdoor feeding among residual malaria vector populations following increased use of insecticide-treated nets in rural Tanzania (cited 800×)
  68. W2166231658: The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic précis (cited 794×)
  69. W2162714623: The dominant Anopheles vectors of human malaria in the Asia-Pacific region: occurrence data, distribution maps and bionomic précis (cited 583×)
  70. W2770432019: Genetic diversity of the African malaria vector Anopheles gambiae (cited 477×)
  71. W2340524139: A Preliminary Evaluation of a Recombinant Circumsporozoite Protein Vaccine against Plasmodium falciparum Malaria (cited 884×)
  72. W2169790609: Protection against a Malaria Challenge by Sporozoite Inoculation (cited 585×)
  73. W2038910210: Efficacy of the RTS,S/AS02A vaccine against Plasmodium falciparum infection and disease in young African children: randomised controlled trial (cited 756×)
  74. W2108476551: First Results of Phase 3 Trial of RTS,S/AS01 Malaria Vaccine in African Children (cited 914×)
  75. W2244674613: A Phase 3 Trial of RTS,S/AS01 Malaria Vaccine in African Infants (cited 768×)
  76. W3158165973: Efficacy of a low-dose candidate malaria vaccine, R21 in adjuvant Matrix-M, with seasonal administration to children in Burkina Faso: a randomised controlled trial (cited 466×)
  77. W4386054294: Seasonal vaccination with RTS,S/AS01E vaccine with or without seasonal malaria chemoprevention in children up to the age of 5 years in Burkina Faso and Mali: a double-blind, randomised, controlled, phase 3 trial (cited 69×)
  78. W4367318132: The Matrix-M™ adjuvant: A critical component of vaccines for the 21 st century (cited 116×)
  79. W4295633071: Efficacy and immunogenicity of R21/Matrix-M vaccine against clinical malaria after 2 years' follow-up in children in Burkina Faso: a phase 1/2b randomised controlled trial (cited 296×)
  80. W4391872850: The public health impact and cost-effectiveness of the R21/Matrix-M malaria vaccine: a mathematical modelling study (cited 50×)
  81. W2051317473: The African Genome Variation Project shapes medical genetics in Africa (cited 696×)
  82. W2075817888: Common West African HLA antigens are associated with protection from severe malaria (cited 1,573×)
  83. W2137935465: G6PD Deficiency Prevalence and Estimates of Affected Populations in Malaria Endemic Countries: A Geostatistical Model-Based Map (cited 584×)
  84. W2022307600: Enhanced phagocytosis of ring-parasitized mutant erythrocytes: a common mechanism that may explain protection against falciparum malaria in sickle trait and beta-thalassemia trait (cited 357×)
  85. W65176043: Early Phagocytosis of Glucose-6-Phosphate Dehydrogenase (G6PD)-Deficient Erythrocytes Parasitized by Plasmodium falciparum May Explain Malaria Protection in G6PD Deficiency (cited 326×)
  86. W4311573178: A randomized controlled trial showing safety and efficacy of a whole sporozoite vaccine against endemic malaria (cited 53×)
  87. W4395699463: Subcutaneous Administration of a Monoclonal Antibody to Prevent Malaria (cited 88×)
  88. W2891027664: A CRISPR–Cas9 gene drive targeting doublesex causes complete population suppression in caged Anopheles gambiae mosquitoes (cited 974×)
  89. W2017380332: Implication of the Mosquito Midgut Microbiota in the Defense against Malaria Parasites (cited 840×)
  90. W2111179758: A Research Agenda to Underpin Malaria Eradication (cited 674×)
  91. W2786896727: malERA: An updated research agenda for diagnostics, drugs, vaccines, and vector control in malaria elimination and eradication (cited 125×)
  92. W2161535656: The changing epidemiology of malaria elimination: new strategies for new challenges (cited 717×)
  93. W2110243445: Malaria: progress, perils, and prospects for eradication (cited 701×)
  94. W2725449842: Malaria in Brazil, Colombia, Peru and Venezuela: current challenges in malaria control and elimination (cited 355×)
  95. W1978231049: Climate change and mosquito-borne disease. (cited 764×)
  96. W1903506013: Impact of climate change on human infectious diseases: Empirical evidence and human adaptation (cited 1,053×)