Skip to main content
  • Loading metrics

Multiple blood feeding in mosquitoes shortens the Plasmodium falciparum incubation period and increases malaria transmission potential

  • W. Robert Shaw ,

    Contributed equally to this work with: W. Robert Shaw, Inga E. Holmdahl

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliation Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America

  • Inga E. Holmdahl ,

    Contributed equally to this work with: W. Robert Shaw, Inga E. Holmdahl

    Roles Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliations Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America, Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America

  • Maurice A. Itoe,

    Roles Conceptualization, Investigation, Project administration, Validation, Writing – review & editing

    Affiliation Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America

  • Kristine Werling,

    Roles Conceptualization, Investigation, Project administration, Validation, Writing – review & editing

    Affiliation Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America

  • Meghan Marquette,

    Roles Investigation, Resources, Validation, Writing – review & editing

    Affiliation Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America

  • Douglas G. Paton,

    Roles Conceptualization, Formal analysis, Validation, Writing – review & editing

    Affiliation Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America

  • Naresh Singh,

    Roles Investigation, Methodology, Resources, Writing – review & editing

    Affiliation Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America

  • Caroline O. Buckee,

    Roles Conceptualization, Formal analysis, Supervision, Visualization, Writing – original draft, Writing – review & editing

    Affiliations Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America, Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America

  • Lauren M. Childs ,

    Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing (LMC); (FC)

    Affiliation Department of Mathematics, Virginia Tech, Blacksburg, Virginia, United States of America

  • Flaminia Catteruccia

    Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing (LMC); (FC)

    Affiliation Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America


Many mosquito species, including the major malaria vector Anopheles gambiae, naturally undergo multiple reproductive cycles of blood feeding, egg development and egg laying in their lifespan. Such complex mosquito behavior is regularly overlooked when mosquitoes are experimentally infected with malaria parasites, limiting our ability to accurately describe potential effects on transmission. Here, we examine how Plasmodium falciparum development and transmission potential is impacted when infected mosquitoes feed an additional time. We measured P. falciparum oocyst size and performed sporozoite time course analyses to determine the parasite’s extrinsic incubation period (EIP), i.e. the time required by parasites to reach infectious sporozoite stages, in An. gambiae females blood fed either once or twice. An additional blood feed at 3 days post infection drastically accelerates oocyst growth rates, causing earlier sporozoite accumulation in the salivary glands, thereby shortening the EIP (reduction of 2.3 ± 0.4 days). Moreover, parasite growth is further accelerated in transgenic mosquitoes with reduced reproductive capacity, which mimic genetic modifications currently proposed in population suppression gene drives. We incorporate our shortened EIP values into a measure of transmission potential, the basic reproduction number R0, and find the average R0 is higher (range: 10.1%–12.1% increase) across sub-Saharan Africa than when using traditional EIP measurements. These data suggest that malaria elimination may be substantially more challenging and that younger mosquitoes or those with reduced reproductive ability may provide a larger contribution to infection than currently believed. Our findings have profound implications for current and future mosquito control interventions.

Author summary

In natural settings the female Anopheles gambiae mosquito, the major malaria vector, blood feeds multiple times in her lifespan. Here we demonstrate that an additional blood feed accelerates the growth of Plasmodium falciparum malaria parasites in this mosquito. Incorporating these data into a mathematical model across sub-Saharan Africa reveals that malaria transmission potential is likely to be higher than previously thought, making disease elimination more difficult. Additionally, we show that control strategies that manipulate mosquito reproduction with the aim of suppressing Anopheles populations may inadvertently favor malaria transmission. Our data also suggest that parasites can be transmitted by younger mosquitoes, which are less susceptible to insecticide killing, with negative implications for the success of insecticide-based strategies.


Malaria remains a devastating disease for tropical and subtropical regions, accounting for an estimated 405,000 deaths and 228 million cases in 2018 [1]. Anopheles mosquitoes transmit the causative Plasmodium malaria parasites, and malaria control strategies aimed at the mosquito vector through long-lasting insecticide-treated bed nets (LLINs) and indoor residual spraying (IRS) have greatly decreased the malaria burden in recent decades. Despite this progress, a deeper understanding of the impact of complex mosquito behaviors on the transmission potential of mosquito populations is needed to generate better predictions of disease transmission and of the efficacy of control interventions. This need is all the more urgent given that the reduction in malaria cases has plateaued in the past few years [1], possibly due to the reduced efficacy of LLINs and IRS in the face of insecticide resistance spreading in mosquitoes [2].

A key determinant of malaria transmission is the significant length of time it takes for Plasmodium parasites to develop from sexual stages in the mosquito blood meal into infectious sporozoites in the salivary glands, a time period known as the extrinsic incubation period or EIP. As mosquito survival must exceed the EIP for onward transmission to humans to occur, this parameter has an important relationship to mosquito mortality. This is one reason why life-shortening insecticidal interventions like LLINs emerge as particularly effective in epidemiological models (in addition to lowering mosquito densities and biting rates [35]).

In most epidemiological studies the Plasmodium falciparum EIP is considered to last 12–14 days [68]. This is similar to the expected lifespan of the Anopheles female, which, although difficult to measure precisely due to the lack of reliable age markers, has been shown to be approximately 10–20 days [911]. The biological factors that influence parasite developmental rates and ultimately the EIP are starting to become elucidated. The EIP has been shown to depend on environmental temperature and larval nutrition, with higher temperatures (up to a point) and plentiful nutrients available during larval stages accelerating parasite growth [8,1216]. Our recent studies in Anopheles gambiae, one of the most effective malaria vectors in sub-Saharan Africa, have shown the P. falciparum EIP is also dependent on mosquito oogenesis, a process largely orchestrated by the steroid hormone 20-hydroxyecdysone (20E) [17]. When we reduced egg development using several means, including impairing 20E function and decreasing lipid mobilization, we detected the presence of larger oocysts in the midgut, as measured by averaging their cross-sectional area following mercurochrome staining. In turn, this led to infectious sporozoites reaching the salivary glands at earlier time points, leading to a shorter EIP [17]. Furthermore, faster oocyst growth in conditions of reduced egg development was characterized by the accumulation of neutral lipids in the midgut and was reversed by depleting the major lipid transporter Lipophorin (Lp), suggesting that excess lipids that are not mobilized from the midgut mediate accelerated development. In agreement with this observation, a negative correlation between mean oocyst size and egg numbers indicated that parasites effectively exploit available mosquito resources for growth following egg development [17].

Given this unexpected relationship between oogenesis and the P. falciparum EIP, additional blood meals a female takes in order to complete further cycles of egg development may have important consequences for parasite transmission. Indeed, many mosquito species, including An. gambiae, naturally undergo multiple reproductive cycles of blood feeding, egg development and egg laying in their lifespan, which can be counted by ovarian dilatations [18,19]. Moreover, multiple feeds may be required even within a single reproductive cycle due to interrupted feeding or to nutrient deprivation during the larval stage (pre-gravid behavior) [20]. Additional blood meals may therefore potentially influence oocyst growth and the EIP, as suggested by reports showing an additional feed can increase P. falciparum oocyst size [21,22] and salivary gland sporozoite numbers at a given time point [22,23], and can be employed to boost sporozoite yields [2426].

Here, we examine how parasite development is affected by multiple feedings, and illustrate the consequences of these effects using a simple epidemiological model of malaria transmission potential. By providing a second uninfected blood meal to females previously infected with P. falciparum, we show a striking increase in oocyst growth rates, which causes faster accumulation of sporozoites in the salivary glands and a substantially shortened EIP. When considered in the context of the basic reproduction number (R0)—the average number of infections resulting from a first case—this shortened EIP leads to a consistent increase in malaria transmission potential in sub-Saharan Africa. Accelerated growth after an additional feeding event is not mediated by Lp-transported lipids, but is further enhanced in reproduction-defective females, suggesting that mosquito control strategies that reduce the reproductive output of Anopheles females—such as population suppression gene drives—could actually favor parasite transmission. These data have important implications for accurately understanding malaria transmission potential and estimating the true impact of current and future mosquito control measures.


An additional blood meal accelerates P. falciparum oocyst development in an Lp-independent manner

We set out to determine the potential effects of a second blood feeding on parasite development, and whether any of these effects might be mediated by the lipid transporter Lp. To achieve this, we injected An. gambiae females with double-stranded RNA (dsRNA) targeting Lp (dsLp) and compared them to control females injected with dsRNA targeting green fluorescent protein (dsGFP) (S1 Fig). After allowing females to mate, we blood fed them on a P. falciparum (NF54) culture and provided them with the opportunity to lay eggs, and then, at 3 days (d) post infectious blood meal (pIBM), we gave them an additional, uninfected blood feed (2BF groups, Fig 1A). By this time, females have completed their first gonotrophic cycle and are therefore ready to feed again to produce a second egg batch. For comparison, feeding control groups were instead maintained on sugar after the initial infectious feed (1BF groups, Fig 1A). We dissected females from all four groups (dsGFP 1BF; dsGFP 2BF; dsLp 1BF; dsLp 2BF) at 7 d pIBM, and analyzed oocyst numbers and size by fitting linear mixed models incorporating the number of blood feeds, dsRNA injection and their interaction as fixed effects, and replicate as a random effect (S1 Table). While we detected no effects on the prevalence (χ2 test, S3 Table) or intensity of infection (Fig 1B, prevalence shown in pie charts), we observed a striking increase in oocyst area in females that had been blood fed a second time, measured by averaging the cross-sectional area of up to 50 mercurochrome-stained oocysts in each midgut (Fig 1C). Median oocyst size was 94% larger in these females (model: #BF: p<0.0001), suggesting increased parasite growth rates following an additional blood meal. However, increased oocyst size was not mediated by Lp-transported lipids, as after a second blood meal oocysts in Lp-silenced females showed an increase in size comparable to those in dsGFP females (model: dsRNA: n.s.; Fig 1C). Lp silencing did reduce oocyst numbers, but without affecting prevalence, as previously observed after a single blood meal (model: dsRNA: p<0.0001; Fig 1B) [17,27].

Fig 1. A second blood meal increases oocyst size in a Lp-independent manner.

(A) dsGFP (Cntrl)- and dsLp-injected females were infected with P. falciparum 3 days post injection (inj) and then either provided a second uninfected blood meal 3 days post infectious blood meal (d pIBM) (two red circles) or maintained on sugar (one red circle). Infection outcomes in all groups were determined at 7–14 d pIBM (arrows). (B) Oocyst prevalence (P, pie charts) (χ2 test: χ2 = 4.3, d.f. = 3, n.s.) and intensity (Linear mixed model; FDR-corrected post-hoc Student’s t tests shown for all models) are not affected by a second blood meal at 3 d pIBM (#BF: n.s.), but intensity is lower in Lp-depleted groups (dsRNA: p<0.0001). (C) Oocyst size at 7 d pIBM is significantly increased in females fed twice in both injection groups (Linear mixed model; #BF: p<0.0001; dsRNA: n.s.). Horizontal bars indicate median values. n = numbers of mosquitoes analyzed from 3 different experiments. n.s. = not statistically significant. See S1S4 Tables for details of statistical models.

We next performed immunofluorescence microscopy to assess the developmental stage of these oocysts using a DNA stain and an antibody recognizing the P. falciparum circumsporozoite surface protein (CSP), which is expressed during late oocyst development and on sporozoites [28]. At 8 d pIBM, while oocysts developing in females fed once had DNA but no detectable CSP staining, oocysts derived from females that had fed twice already showed increased DNA content and detectable CSP expression (Fig 2A and 2B), consistent with additional rounds of DNA replication and the beginning of sporozoite formation. Remarkably, by 10 d pIBM, some oocysts in this group were already releasing mature CSP-labelled sporozoites (Fig 2C). Together these data show that P. falciparum development is accelerated when females blood feed a second time, and that accelerated growth is not significantly mediated by the lipid transporter Lp.

Fig 2. A second blood meal accelerates oocyst development.

(A–B) Immunofluorescence assay of oocysts from control females (A) fed once (one red circle) or (B) fed twice (two red circles) at 8 d pIBM. (C) Oocyst from a female fed twice showing the release of mature sporozoites at 10 d pIBM. Sporozoites are labelled with circumsporozoite protein CSP (magenta) and DNA is stained with DAPI (gray). In all panels, scale bar = 10 μm.

Mosquitoes are infectious sooner following an additional blood meal

Accelerated parasite development suggests that mosquitoes may become infectious sooner following an additional blood meal, with consequences for their transmission potential. We therefore compared the timing of the appearance of sporozoites, the infectious stage of parasite development, in dissected salivary glands over the course of several days of sporogony in dsGFP-injected females fed once or twice. Following a similar protocol of a second blood meal at 3 d pIBM, we detected sporozoites as early as 7 d pIBM, and we observed a significant increase in sporozoite prevalence at 8 d pIBM—an early time for sporozoite invasion of the salivary glands—when we detected sporozoites in 33% of control 2BF females compared to 3% in control 1BFs (Fig 3A). This significant increase was still evident at 10 d pIBM, with 84% of dsGFP 2BF mosquitoes harboring sporozoites compared to 40% of 1BF females (Fig 3A). We calculated that females were 15-fold and 7.7-fold, respectively, more likely to have sporozoites in their salivary glands at these early time points if they had had an additional blood meal (χ2 test; 8d: p = 0.0018; 10d: p<0.0001; S3 and S4 Tables). Moreover, the intensity of infection was also increased at 10 d pIBM (model: #BF: p = 0.0001; Fig 3B, S1 and S2 Tables), where we observed a number of highly infected mosquitoes (>10,000 sporozoites/salivary glands), but low prevalence in the singly fed groups prevented statistical testing at 8 d pIBM (S2 Fig). These observations were not due to a change in the prevalence or intensity of oocyst infection, which were both unaffected in dsGFP-injected controls as described above (Fig 1B). By 14 d pIBM 1BF and 2BF mosquitoes became comparably infected, as sporozoites in 1BF mosquitoes had also reached the salivary glands, with sporozoite prevalence near 100% (Fig 3A) and only a significant increase in infection intensity across the 2BF groups (model: #BF: p = 0.034) that did not persist after post-hoc testing (S2 Fig, S1 and S2 Tables).

Fig 3. Mosquitoes are infectious sooner following a second blood meal.

(A–B) Salivary glands of females fed twice (two red circles) show (A) a significantly higher prevalence (P, pie charts) of sporozoites at 8 and 10 d pIBM (χ2 test: 8 d, χ2 = 15, d.f. = 3, p = 0.0018; 10 d, χ2 = 43, d.f. = 3, p<0.0001; FDR-corrected post-hoc χ2 tests shown) and (B) significantly more sporozoites at 10 d pIBM (Linear mixed model; #BF: p = 0.0001; FDR-corrected post-hoc Student’s t tests shown) than females fed once (one red circle). Horizontal bars indicate median values. There is no difference in sporozoite prevalence at a later time point (χ2 test: 14 d, χ2 = 2.4, d.f. = 3, n.s.). (C) The EIP50 (time to 50% infectious–dotted line; values also shown ± 95% C.I.) of control (Cntrl) females fed a second time (blue solid line) is reduced by 2.3 d (21%) compared with controls fed once (orange solid line), as determined from the sporozoite prevalence data shown in (A) (z test, Z = 5.7, p<0.0001). Similarly, EIP50 is reduced by 2.4 d (20%) in Lp-depleted females fed a second time (purple dashed line) compared to those fed once (red dashed line) (z test, Z = 5.3, p<0.0001). Fitted logistic curves (lines), EIP50 ± 95% C.I. (shaded). n = numbers of mosquitoes analyzed from 4 different experiments. n.s. = not statistically significant. See S1S4 Tables for details of statistical models.

Consistent with the observed lack of effects on oocyst growth (Fig 1C), Lp-silenced females behaved as the dsGFP controls and also showed a striking increase in prevalence of infection after a second blood meal (Fig 3A, 3B and S2 Fig). Although the reduced oocyst numbers lowered total sporozoite intensities at 14 d pIBM (model: dsRNA: p = 0.0053), again this difference was not significant after post-hoc testing (S2 Fig).

To compare the rates of parasite development between our treatment groups, we constructed EIP curves based on the above prevalence data using logistic regression to describe over time how an additional blood meal changes the infectiousness of mosquitoes (S3 Table). From these curves, we calculated the EIP50—the point at which half of the mosquitoes become infectious, or in other words the median time until the appearance of sporozoites in the salivary glands—for each treatment group. An additional blood feeding significantly shortened the EIP50, with dsGFP 2BF mosquitoes becoming infectious 2.3 ± 0.4 d earlier than dsGFP 1BF (Z test: p<0.0001; S4 Table), corresponding to a 21% reduction in EIP (Fig 3C, solid lines). Larger oocyst size at 7 d pIBM is therefore associated with shorter estimates for the EIP, as previously shown [17]. Similar results were obtained in Lp-depleted females (2.4 ± 0.4 d; 20% reduction; p<0.0001), confirming that neutral lipids carried by this transporter do not mediate increased parasite growth after a second blood feeding event (Fig 3C, dashed lines). Given mosquitoes regularly take multiple (>3) blood meals in the field [9,29], these results suggest that transmission is likely to occur much sooner than previously thought, and is therefore also mediated by younger mosquitoes.

Modelled estimates of R0 with a single blood meal underestimate transmission

To illustrate the relevance of these results for malaria transmission, we chose a simple metric of transmission potential—the basic reproductive number R0, calculated as a function of temperature [30]. We mapped the consequence of a second blood meal on the distribution of R0 across sub-Saharan Africa, considering all locations where An. gambiae and closely related Anopheles vectors are present. We chose to use this particular temperature-dependent model formulation because R0 depends exponentially on the EIP and the mosquito death rate, which are both influenced by temperature. To avoid over-extrapolating our laboratory data, we estimated R0 in locations within a narrow temperature range (27 ± 2°C) around our experimental conditions (see Materials and Methods).

For each 5x5 km grid cell of the map, we calculated both the standard R0 using EIP50 estimates derived from a single blood feed and the adjusted R0 () using the proportional reduction in EIP50 observed in our dsGFP 2BF females (21%). We then mapped the ratio of the adjusted to standard R0 in each grid cell across sub-Saharan Africa for each month of the year within our temperature range. The number of months that mean monthly temperature falls within this range are presented (Fig 4A). The area within this temperature range for at least one month of the year is home to nearly 738 million people, roughly half of the population in Africa.

The reduction in EIP50 leads to higher modeled mean R0 in all mapped locations. The average increase in R0 is 10.5% (range: 10.1%–12.1%) across all regions of sub-Saharan Africa with at least one month with a mean temperature within 27 ± 2°C (Fig 4B). This result implies that epidemiological models directly incorporating currently accepted EIP parameters may be systematically underestimating malaria transmission potential across a substantial fraction of sub-Saharan Africa.

Fig 4. Relative R0 values across sub-Saharan Africa show increase in malaria transmission potential.

(A) Regions of sub-Saharan Africa with 1 to 12 months of average temperature in 27 ± 2°C. Our modeling analysis was restricted to locations and months of the year during which the average temperature was in this range, in order to align with our laboratory conditions. Areas in gray depict regions where there are 0 months with average temperature in that range, or where the predicted probability of An. gambiae complex is less than 5%. (B) The percent increase of using revised estimates of EIP50 (derived from two blood feeds) to R0 using the standard estimates of EIP50 (derived from a single blood feed). Models using a standard EIP parameter may underestimate R0 by an average of least 10.1%. In these regions, the average change during the months within the relevant temperature range is 10.5% (range: 10.1%–12.1%).

Effects of an additional blood meal are exacerbated in females with impaired egg development

We have previously shown that in females blood fed once, parasite development is substantially faster in multiple instances where oogenesis is reduced [17]. As mosquito reproduction is a target of genetic control strategies currently in the pipeline [31,32], we went on to determine whether parasite growth could be further boosted after a second blood meal in females with impaired egg development. To this aim, we used genetically modified An. gambiae mutants that are mosaics of zero population growthzpg), a gene required for germline cell maintenance whose disruption in females causes severely atrophied ovaries [17,33]. After infecting Δzpg or control females with P. falciparum, we replicated the experimental design described above and provided an additional blood meal to approximately half of each group to compare parasite development in both feeding regimes. Median oocyst size was increased in Δzpg females fed either once or twice when compared to controls (model: #BF: p<0.0001, genotype: p<0.0001; Fig 5A, S1 and S2 Tables), confirming that P. falciparum growth can be further boosted in this background, while oocyst prevalence was unaffected (Fig 5B, pie charts). Despite lower oocyst numbers (genotype: p<0.0001; Fig 5B), sporozoite intensity in the salivary glands at an early time point (10 d pIBM) was higher in Δzpg females than in controls under both feeding regimes, and significantly so after one blood feed (model: #BF: p<0.0001, genotype: p = 0.0056; Fig 5C). Moreover, sporozoite prevalence at 10 d pIBM was significantly higher in Δzpg females fed once (χ2 test; p<0.0001; Fig 5C, upper pie charts). Finally, cumulative prevalence across both single and double blood feedings was significantly increased (Fisher’s exact test: p<0.0001) and these mutants were 3.9-fold more likely to have sporozoites in their salivary glands than control mosquitoes (odds ratio; 95% CI: 2.3–6.5 fold; Fig 5C, lower pie charts). These results suggest that, even in cases where they may support lower oocyst loads, females with impaired egg development might be more effective at transmitting P. falciparum parasites under either blood feeding regime.

Fig 5. Parasite developmental rates are further enhanced in eggless mosquitoes.

(A) Oocysts are significantly larger in Δzpg (eggless) mutant females at 7 d pIBM after both one or two blood meals (Linear mixed model; #BF: p = 0.0001; genotype: p<0.0001; FDR-corrected post-hoc Student’s t tests shown for all models) compared to controls (Cntrl). (B) Oocyst intensities are lower in Δzpg mutant females compared to controls (Linear mixed model; #BF: p = 0.041; genotype: p<0.0001), whereas oocyst prevalence (P, pie charts; χ2 test: χ2 = 6.5, d.f. = 3, n.s.) is unaffected. (C) Salivary glands sporozoite numbers are increased in both control and Δzpg mutant females at 10 d pIBM after a second blood meal (Linear mixed model; #BF: p<0.0001; genotype: p = 0.0056), with sporozoite prevalence (P, upper pie charts) also increased in the Δzpg mutant background (χ2 test, χ2 = 81, d.f. = 3, p<0.0001), significantly at the first blood meal. Pooling data shows higher sporozoite prevalence in Δzpg mutant population (P, lower pie charts) (Fisher’s exact test). Horizontal bars indicate median values. n = numbers of mosquitoes analyzed from 3 (A and B) or 4 (C) different experiments. n.s. = not statistically significant. See S1S4 Tables for details of statistical models.


The parasite EIP is a key parameter in malaria transmission dynamics. Given the relatively short Anopheles lifespan—estimated to be around 10–20 days depending on species and environmental conditions [911]—parasites with faster sporogonic development are more likely to be transmitted to the next human host [4]. Here, we demonstrate that multiple blood feedings significantly accelerate parasite growth, shortening the time required for sporozoites to appear in the salivary glands. These findings are consistent with infection studies in closely related mosquito species that showed that an additional blood meal during development either boosts P. falciparum sporozoite intensities or yields [2226,34] or increases oocyst size [2123], although none analyzed parasite growth rates after the second meal. Our study conclusively links the effects of an additional blood meal to increased parasite developmental rates and a shortened EIP. Future work should determine whether additional feeding events during the same gonotrophic cycle also impact P. falciparum growth, or whether the presence of parasites in a second blood meal would affect the development of already established parasites.

How does this accelerated development occur? An additional blood meal provides the female mosquito with greater nutrient resources, especially amino acids and lipids, that both could be potentially transported across the oocyst membrane. Parasites require lipids to generate phospholipid-containing membranes for subdivision into thousands of sporozoites, rather than for energy (as they seem to lack canonical enzymes for β-oxidation [35]). Oocysts can take up labelled mosquito lipoparticles [36], and increased availability of lipids as provided by an additional blood meal may accelerate host lipid scavenging, which also occurs during human stages of infection [3739]. In this study, however, depletion of Lp—the major mosquito lipid transporter—did not slow rates of oocyst growth or sporozoite appearance after a second blood feeding, with only a slight, non-significant delay in EIP50 detected, suggesting that other nutrients (possibly amino acids, as suggested by a recent report [21]) may mediate the bulk of the observed boost in oocyst development. Lp silencing also had no effects on P. falciparum oocyst growth in females fed once (Fig 1C) [17], contrary to observations in the mouse malaria model P. berghei [40,41]. Interestingly, however, in our previous studies we showed that Lp-transported lipids do mediate the accelerated growth observed in conditions of reduced egg numbers, likely linked to the observed accumulation of lipids in the midgut in those females [17]. Combined, these results point to a remarkable plasticity in P. falciparum parasites in utilizing mosquito nutrients for growth depending on the metabolic state of the Anopheles female, and suggest fundamental differences in the mechanisms mediating development of human versus rodent malaria parasites. In future studies it will be interesting to ascertain the mechanisms behind the reduced oocyst numbers observed in Lp-depleted females, and if those are similar to the mechanisms induced in Δzpg mutants.

Consistent with accelerated oocyst growth and maturation, we observed an earlier presence of sporozoites in the salivary glands and a significant decrease in the EIP. Considering females blood feed on average every 2–3 days [9], and thus have taken >2 meals by the time they become infectious [29], our results may represent a conservative estimate of the impact of feeding behavior on the EIP. Indeed, our data using Δzpg mutants demonstrate that P. falciparum growth rates are not saturated with two blood feeds and that parasites are capable of undergoing even shorter developmental cycles in the mosquito vector. Although we did not see a significant increase in sporozoite intensities in Δzpg females fed twice compared to controls under the same feeding regime, we observed a number of females at 10 d pIBM with very high infection intensities (>10,000 sporozoites/salivary glands) (Fig 5C). Based on a recent report demonstrating a similar intensity threshold is required for infectivity of P. yoelii sporozoites to the mammalian host [42], our data suggest the earlier appearance of more highly infected mosquitoes may increase the force of transmission, especially if a few highly infected mosquitoes are the primary drivers of transmission. However, the overall impact of additional blood meals in malaria endemic areas will likely also depend on other environmental factors affecting lifespan and blood feeding frequency.

One caveat of our study is that we measured the effects of an additional blood meal only in An. gambiae and we cannot exclude that the magnitude of the decrease in EIP will be different in other AnophelesPlasmodium combinations. Additional blood meals, however, have been shown to shorten the dengue virus EIP [43], improve Leishmania transmission [44], accelerate filarial worm development [45] and increase La Crosse virus replication [46]. All these findings suggest that exploiting mosquito resources may be a generalized mechanism for pathogens to plastically accelerate their development and improve their odds of transmission.

While transmission efficiency may be assessed directly from epidemiological data surveys [47], estimations of potential interventions require models informed by entomological data. Incorporating our shortened EIP into a simple model of malaria R0 to reflect multiple blood feeding, we see the R0 increases by an average of 10.5% across much of sub-Saharan Africa. The neglected contribution of multiple blood feeding may partly explain higher malaria burdens in places and seasons when estimated transmission potential is low [48]. Moreover, underestimates of malaria transmission potential would suggest that malaria elimination efforts in many settings may be more challenging than anticipated. One limitation is our choice of the basic reproductive number, which considers mean-field dynamics, without accounting for known heterogeneities such as differences in mosquito lifespan, parasite strain competition and spatial variation [49]. While these heterogeneities play a role in determining the precise level of transmission, we expect them to affect our transmission estimates equivalently and in the same direction under both single and multiple blood feeds. Thus, in our calculation of the ratio of R0s to estimate the impact of a second blood feeding, the effect of these heterogeneities in a given location will cancel out. Importantly, although many estimates of R0 are derived from prevalence and thus may not directly incorporate EIP, others do explicitly use this parameter and thus may be systematically underestimating its relevance.

What are the implications of these findings for vector control strategies? Firstly, our data point towards females potentially contributing to malaria transmission from a younger age. Given the observed age-dependent mortality induced by insecticides, with higher resistance levels observed in younger mosquitoes [50,51], this observation implies that current models of insecticide-based interventions (both LLINs and IRS) need to be revisited. When combined with the observation that multiple blood feeding increases insecticide resistance in older females of a related species, An. arabiensis [52], our results suggest that mosquitoes feeding multiple times are more likely to survive to the point when they become infectious. Previous work has similarly predicted a lesser effectiveness for mosquito control methods targeting survival when the EIP is shorter [53].

Secondly, our results obtained with Δzpg mutants show that—due to a further increase in parasite growth rates—mosquitoes with reduced reproductive capacity have a significantly higher transmission potential, even in the face of possible lower oocyst numbers. These findings are particularly relevant for control strategies that tamper with mosquito reproduction, such as genetically-engineered population suppression gene drives [31,32]. At a time when Anopheles gene drive strains are being tested in semi-field settings, our data call for a careful evaluation of whether these genetically-modified mosquitoes would contribute to more efficient malaria transmission while the drive is spreading.

Finally, our results emphasize that informed policy decisions on current and future malaria control strategies can only be built on thorough research into the fundamental factors affecting malaria transmission biology.

Materials and methods

Rearing of Anopheles gambiae mosquitoes

Anopheles gambiae mosquitoes (wild-type G3 and transgenic strains) were reared in cages at 27°C, 70–80% humidity on a 12 h light:12 h dark cycle. Adults in colony cages were fed on 10% glucose solution ad libitum and weekly on human blood (Research Blood Components, Boston, MA). Males and females were sexed as pupae and mated in large cages.

Plasmodium falciparum (NF54 strain) was cultured as in [17] and is used under the permissions of a material transfer agreement from the laboratory of Carolina Barillas-Mury, National Institutes of Health, Bethesda, MD, USA.

Gene expression knockdown using dsRNA

PCR fragments of the eGFP control (495 bp) and Lp (600 bp) were amplified from plasmids pCR2.1-eGFP and pLL10-Lp, as described previously [17,54] and verified by DNA gel electrophoresis. dsRNA was transcribed and purified from the PCR templates using the Megascript T7 transcription kit (Thermo Fisher Scientific) as described previously [55]. 690 ng of dsRNA (dsGFP, dsLp) was injected (Nanoject II, Drummond) at a concentration of 10 ng/nl into adult G3 females within 1 day (d) of eclosion. Females were randomly assigned to injection groups and surviving females were mated with G3 males and used in subsequent experiments. Gene knockdown levels were determined in at least 3 biological replicates by RNA extraction, cDNA synthesis and quantitative real-time PCR at 6 d post injection as described in [17].

P. falciparum infections of An. gambiae mosquitoes

Cages of mated female mosquitoes aged 4 d (or 4–6 d for transgenic mosquitoes) were blood fed on ~320 μl P. falciparum culture for 30–60 min via heated membrane feeders and introduced into a custom-built glove box (Inert Technology, Amesbury, MA). Feeding behavior was encouraged by starving mosquitoes of 10% glucose solution for 24 h and females not fully engorged were removed. Blood-fed mosquitoes were provided 10% glucose solution for 48 h and then given an oviposition site. Females were fed a second time 3 d after the initial infectious blood meal, using uninfected blood. Blood intake at the second blood meal was encouraged by providing an oviposition site 2 d post infectious blood meal (pIBM) and non-blood fed mosquitoes were removed. Females blood-fed twice and control mosquitoes fed once were provided 10% glucose solution until dissection. At dissection time points, mosquitoes were aspirated into 80% ethanol and transferred to 1X phosphate-buffered saline (PBS) (oocyst stages) or aspirated into ice-cold PBS (sporozoites stages) and beheaded. At least 3 biological replicates of each infection were performed.

Oocyst counts and measurements: At 7 d pIBM, midguts were stained directly in 2 mM mercurochrome (Sigma-Aldrich, St. Louis, MO) for 12 min. Mercurochrome-stained midguts were imaged at 100X on an Olympus Inverted CKX41 microscope, and oocysts were counted and measured using scaled images in FIJI [56]. Burst oocysts were counted but excluded from oocyst size analysis. Mean oocyst size was calculated for each midgut to avoid pseudoreplication.

Oocyst staining: At 8 and 10 d pIBM, midguts were fixed in 4% formaldehyde for 30–40 min, permeabilized and blocked for 1 h in PBS, 0.1% Triton (PBS-T), 1% bovine serum albumin (BSA) at 22°C, and stained with an anti-CSP mouse monoclonal 2A10 (BEI Resources)(1:350), followed by a goat anti-mouse-Alexa 488 secondary antibody (Molecular Probes)(1:1000). Samples were washed in PBS-T, stained with DAPI (1 μg/ml) and mounted in Vectashield with DAPI (Vector Laboratories, Burlingame, CA), and then imaged at 630X on a Zeiss Inverted Observer Z1 with Apotome2. Scaled images were processed in FIJI.

Sporozoite counts: Mosquitoes were decapitated and the salivary glands of individual females were collected in a small volume of PBS and disrupted using a handheld disposable pestle. Released sporozoites were spun at 8000 g for 10 min at 4°C and resuspended in a known volume of PBS. Sporozoites in 0.1 μl were counted using a disposable hemocytometer at 200X magnification on an Olympus Inverted CKX41 microscope with phase-contrast microscopy and sporozoite totals for each mosquito were calculated.

Generation of Δzpg females

Zpg and Cas9-carrying mosquito strains were generated previously [17]. Zpg/Cas9 mutant females, hereafter Δzpg mutants, were the F1 progeny of Zpg and Cas9 transgene homozygotes. Zpg controls and Δzpg mutant females were mated to G3 males prior to infection, and did not differ in their ability to take a blood meal.

Statistical analysis

Experimental data were analyzed using JMP 14 Pro statistical software and GraphPad Prism 8.0. JMP 14 Pro was used to construct statistical models to account for variation due to multiple factors in an experiment. Residual Maximum Likelihood (REML) variance components analysis was used by fitting linear mixed models after data transformation to normality. The number of blood feeds, dsRNA injection or genotype and their interaction were used as fixed effects and replicate was included as a random effect. Model effect test outputs are reported and multiple comparisons were calculated using 4 pairwise Student’s t tests followed by FDR correction (S1 and S2 Tables). Graphpad Prism 8.0 was used to calculate EIP (using logistic regression curves), Z tests, Fisher’s exact tests and χ2 tests (S3 and S4 Tables). A significance value of 0.05 was used as a threshold in all tests.


We used a previously published model [30] of the basic reproductive number, R0, incorporating temperature dependence, to explore the implications of shortening EIP alone on estimated transmission potential. With this model we aimed not to predict R0 across regions considered, but rather to examine how the EIP could impact R0 estimates. To minimize the extrapolation of our laboratory experiments, we estimate R0 in locations within a narrow temperature range (27 ± 2°C) around our experimental conditions.

To demonstrate the impact of a shorter EIP on R0, we use equation (2) from [30] simplified here as where f(T) and g(T) are functions of temperature-dependent trait data from Anopheles species and g(T) depends linearly on EIP (S1 Text, S3 Fig, S5 and S6 Tables). We then modified the basic reproductive number to incorporate a second blood feeding by scaling EIP using the term β, which we refer to as given by

We determine the scaling parameter β as the relative reduction in EIP in the presence of a second blood feed: β = 8.63 (2BF)/10.88 (1BF) = 0.793. The change in R0 using a shortened EIP is shown by the ratio of the modified R0 to the original R0 as (S4 Fig). To estimate the impact of the EIP reduction on transmission potential, we applied these functions to current human population and monthly mean temperature data across sub-Saharan Africa to estimate the percent change in R0 under a scenario where mosquitoes blood feed while infected. As our laboratory data were collected at 27°C and many of the drivers of malaria transmission are sensitive to temperature, we restricted our R0 projections to the regions and months of the year where the average temperature was 27 ± 2°C (Fig 4A).

We used spatial raster data to calculate the change in R0 across relevant regions of sub-Saharan Africa. We obtained global monthly minimum and maximum temperatures for the period 2010–2018 from TerraClimate [57]. Similar to Fick et al. [58], we calculated the average temperature for each month during this period, by taking the mean of the recorded maximum and minimum temperature. We then determined the average temperature for each calendar month (Jan–Dec) by taking the mean for that month over this nine-year period. We restricted our modeling analysis only to months and locations with mean temperatures between 27 ± 2°C. We further restricted analysis to the regions of Africa where the predicted probability of An. gambiae and closely related species (An. gambiae complex) is greater than 5%, using predicted Anopheles distribution maps from the Malaria Atlas Project [59], under the assumption that the observed effects on the EIP are consistent in these species. Spatial human population distribution for 2020 was obtained from WorldPop [60]. Monthly mean temperature and human population data were aggregated with bilinear resampling to match the projection of the Anopheles geographic extent data at a 5x5 km resolution.

Using these data, we calculated R0 and for each 5x5 km grid cell for each month. We determined the ratio for each month to show the monthly change in transmission potential under a multiple blood feeding scenario (S5 Fig). We considered the mean of the monthly R0 and estimates during months at 27 ± 2°C and examined the ratio of the means. To evaluate the relevance of our results to the population of sub-Saharan Africa, we tallied the total population living in the mapped areas, that is, 5x5 km grid cells with at least one month in the 27 ± 2°C temperature range, and find nearly 738 million people living in these regions.

The modelling code is available on Github at

Supporting information

S1 Fig. Lp expression is effectively silenced following dsRNA injection.

Lp gene expression was determined in pools of 5–10 decapitated females at 6 d post injection (3 d pIBM) at the time of the second blood feed. Lp expression levels were normalized to Rpl19. Four biological replicates were analyzed with means ± standard error shown by horizontal bars. Unpaired t-test.


S2 Fig. Sporozoite intensities in control and Lp-depleted mosquitoes at 8 and 14 d pIBM.

(A) Salivary glands of females fed twice (two red circles) show more sporozoites than females fed once (one red circle) at 8 d but low prevalence in singly-fed groups prevents a determination of statistical significance. (B) Sporozoite levels in salivary glands at 14 d pIBM are comparable between singly and doubly-fed control and Lp-silenced mosquitoes (Linear mixed model; #BF: p = 0.034; dsRNA: p = 0.0053; FDR-corrected post-hoc Student’s t tests shown). Neither the increase in infection intensity across the 2BF groups, nor the decreased sporozoite intensity in Lp-silenced groups persist after post-hoc testing (S1 and S2 Tables). Horizontal bars indicate median values. n = numbers of mosquitoes analyzed from 3 different experiments. n.s. = not statistically significant.


S3 Fig. Anopheles gambiae EFD data fit to a quadratic function.

Data points extracted from Villena et al. [61] were fit to a quadratic function using the nls function in R as described in Mordecai et al. [30]. The fitted quadratic function is shown, with parameters listed in S6 Table.


S4 Fig. The ratio of R0 values is temperature dependent but consistent across temperatures in 27 ± 2°C.

(A) Baseline R0 (orange) and Adjusted (purple) as temperature varies. No numeric scale is given as raw R0 values depend on parameters, such as population size, that are not temperature dependent and cancel out in the R0 ratio. (B) The increase in R0 with shortened EIP as a function of temperature. Within the temperature range 27 ± 2°C, the increase in R0 is between 10.1% and 12.1%.


S5 Fig. Monthly changes in R0 under a multiple blood feeding scenario.

We calculated the monthly changes in R0 for each 5x5 km grid cell by taking the ratio using the mean temperature of each month that has a mean temperature at 27 ± 2°C. The restricted data points shown here are used to create the summary maps in Fig 4.


S1 Table. Statistical models.

JMP 14 Pro statistical software was used to construct models for data analysis to account for multiple variables in an experiment. Residual Maximum Likelihood (REML) variance components analysis was used by fitting linear mixed models after cube-root transformation to resemble a normal distribution. The number of blood feeds, dsRNA injection group and their interaction were used as fixed effects and replicate was included as a random effect. Effect test outputs are reported here. Multiple comparisons were calculated using 4 pairwise Student’s t tests followed by FDR correction (see S2 Table). d pIBM = days post infectious blood meal; #BF = number of blood feeds; FDR = false discovery rate.


S2 Table. Post-hoc testing.

Significant differences in oocyst size and oocyst and sporozoite intensity using an FDR of 0.05. See S1 Table.


S3 Table. Statistical testing for infection prevalence.

GraphPad Prism 8 was used for logistic regression, Fisher’s exact and χ2 tests.


S4 Table. Post-hoc testing.

Significant differences in infection prevalence using an FDR of 0.05. See S3 Table.


S5 Table. Temperature dependent traits fitted with Brière function.

All parameters from Mordecai et al. [30]. See references within.


S6 Table. Temperature dependent traits fitted with quadratic function.

Parameters for bc, p, and pEA from Mordecai et al. [30]. See references within. Parameters for EFD were fit to data published in Villena et al. [61].


S1 Data. Raw data plotted in graphical figures.



We thank Emily Lund, Kate Thornburg, and Emily Selland for help in mosquito rearing, and members of the Catteruccia laboratory for comments on the manuscript.


  1. 1. WHO. World Malaria Report. Geneva: World Health Organization, 2019.
  2. 2. Hemingway J, Ranson H, Magill A, Kolaczinski J, Fornadel C, Gimnig J, et al. Averting a malaria disaster: will insecticide resistance derail malaria control? Lancet. 2016;387(10029):1785–8. Epub 2016/02/18. pmid:26880124; PubMed Central PMCID: PMC6215693.
  3. 3. Ross R. Some Quantitative Studies in Epidemiology. Nature. 1911;87(2188):466–7.
  4. 4. Macdonald G. Epidemiological basis of malaria control. Bull World Health Organ. 1956;15(3–5):613–26. Epub 1956/01/01. pmid:13404439; PubMed Central PMCID: PMC2538278.
  5. 5. Smith DL, Battle KE, Hay SI, Barker CM, Scott TW, McKenzie FE. Ross, macdonald, and a theory for the dynamics and control of mosquito-transmitted pathogens. PLoS Pathog. 2012;8(4):e1002588. Epub 2012/04/13. pmid:22496640; PubMed Central PMCID: PMC3320609.
  6. 6. Vaughan JA, Noden BH, Beier JC. Population dynamics of Plasmodium falciparum sporogony in laboratory-infected Anopheles gambiae. J Parasitol. 1992;78(4):716–24. Epub 1992/08/01. pmid:1635032.
  7. 7. WHO. Manual on Practical Entomology in Malaria. Part II. Methods and Techniques. Geneva: World Health Organization, 1975 9241700130.
  8. 8. Ohm JR, Baldini F, Barreaux P, Lefevre T, Lynch PA, Suh E, et al. Rethinking the extrinsic incubation period of malaria parasites. Parasit Vectors. 2018;11(1):178. Epub 2018/03/14. pmid:29530073; PubMed Central PMCID: PMC5848458.
  9. 9. Gillies MT, Wilkes TJ. A study of the age-composition of populations of Anopheles gambiae Giles and A. funestus Giles in North-Eastern Tanzania. Bull Entomol Res. 1965;56(2):237–62. Epub 1965/12/01. pmid:5854754.
  10. 10. Costantini C, Li SG, Della Torre A, Sagnon N, Coluzzi M, Taylor CE. Density, survival and dispersal of Anopheles gambiae complex mosquitoes in a west African Sudan savanna village. Med Vet Entomol. 1996;10(3):203–19. Epub 1996/07/01. pmid:8887330.
  11. 11. Service MW, Towson H. ‘The Anopheles Vector’ in ‘Essential Malariology’. 4th ed. Warrell DA, Gilles HM, editors. London, UK: Arnold; 2002.
  12. 12. Paaijmans KP, Blanford S, Bell AS, Blanford JI, Read AF, Thomas MB. Influence of climate on malaria transmission depends on daily temperature variation. Proc Natl Acad Sci U S A. 2010;107(34):15135–9. Epub 2010/08/11. pmid:20696913; PubMed Central PMCID: PMC2930540.
  13. 13. Blanford JI, Blanford S, Crane RG, Mann ME, Paaijmans KP, Schreiber KV, et al. Implications of temperature variation for malaria parasite development across Africa. Sci Rep. 2013;3:1300. Epub 2013/02/20. pmid:23419595; PubMed Central PMCID: PMC3575117.
  14. 14. Shapiro LL, Murdock CC, Jacobs GR, Thomas RJ, Thomas MB. Larval food quantity affects the capacity of adult mosquitoes to transmit human malaria. Proc Biol Sci. 2016;283(1834). Epub 2016/07/15. pmid:27412284; PubMed Central PMCID: PMC4947883.
  15. 15. Shapiro LLM, Whitehead SA, Thomas MB. Quantifying the effects of temperature on mosquito and parasite traits that determine the transmission potential of human malaria. PLoS Biol. 2017;15(10):e2003489. Epub 2017/10/17. pmid:29036170; PubMed Central PMCID: PMC5658182.
  16. 16. Suh E, Grossman MK, Waite JL, Dennington NL, Sherrard-Smith E, Churcher TS, et al. The influence of feeding behaviour and temperature on the capacity of mosquitoes to transmit malaria. Nat Ecol Evol. 2020;4(7):940–51. Epub 2020/05/06. pmid:32367033; PubMed Central PMCID: PMC7334094.
  17. 17. Werling K, Shaw WR, Itoe MA, Westervelt KA, Marcenac P, Paton DG, et al. Steroid Hormone Function Controls Non-competitive Plasmodium Development in Anopheles. Cell. 2019;177(2):315–25 e14. Epub 2019/04/02. pmid:30929905; PubMed Central PMCID: PMC6450776.
  18. 18. Clements AN. The Biology of Mosquitoes. London: Chapman & Hall; 1992.
  19. 19. Detinova TS. Age-grouping Methods in Diptera of Medical Importance with Special Reference to Some Vectors of Malaria. Geneva: World Health Organization: 1962. pmid:13885800
  20. 20. Scott TW, Takken W. Feeding strategies of anthropophilic mosquitoes result in increased risk of pathogen transmission. Trends Parasitol. 2012;28(3):114–21. Epub 2012/02/04. pmid:22300806.
  21. 21. Kwon H, Reynolds RA, Simões ML, Dimopoulos G, Smith RC. Malaria parasite immune evasion and adaptation to its mosquito host is influenced by the acquisition of multiple blood meals. bioRxiv. 2019:1–22. Epub 15 Oct 2019.
  22. 22. Habtewold T, Sharma AA, Wyer CAS, Masters EKG, Windbichler N, Christophides GK. Plasmodium oocysts respond with dormancy to crowding and nutritional stress. bioRxiv. 2020:1–17. Epub 09 March 2020.
  23. 23. Ponnudurai T, Lensen AH, van Gemert GJ, Bensink MP, Bolmer M, Meuwissen JH. Sporozoite load of mosquitoes infected with Plasmodium falciparum. Trans R Soc Trop Med Hyg. 1989;83(1):67–70. Epub 1989/01/01. pmid:2690418.
  24. 24. Meredith JM, Basu S, Nimmo DD, Larget-Thiery I, Warr EL, Underhill A, et al. Site-specific integration and expression of an anti-malarial gene in transgenic Anopheles gambiae significantly reduces Plasmodium infections. PLoS One. 2011;6(1):e14587. Epub 2011/02/02. pmid:21283619; PubMed Central PMCID: PMC3026776.
  25. 25. Stone WJ, Eldering M, van Gemert GJ, Lanke KH, Grignard L, van de Vegte-Bolmer MG, et al. The relevance and applicability of oocyst prevalence as a read-out for mosquito feeding assays. Sci Rep. 2013;3:3418. Epub 2013/12/05. pmid:24301557; PubMed Central PMCID: PMC4894383.
  26. 26. Stone W, Grabias B, Lanke K, Zheng H, Locke E, Diallo D, et al. A comparison of Plasmodium falciparum circumsporozoite protein-based slot blot and ELISA immuno-assays for oocyst detection in mosquito homogenates. Malar J. 2015;14:451. Epub 2015/11/18. pmid:26573271; PubMed Central PMCID: PMC4647817.
  27. 27. Mendes AM, Schlegelmilch T, Cohuet A, Awono-Ambene P, De Iorio M, Fontenille D, et al. Conserved mosquito/parasite interactions affect development of Plasmodium falciparum in Africa. PLoS Pathog. 2008;4(5):e1000069. Epub 2008/05/17. pmid:18483558; PubMed Central PMCID: PMC2373770.
  28. 28. Posthuma G, Meis JF, Verhave JP, Hollingdale MR, Ponnudurai T, Meuwissen JH, et al. Immunogold localization of circumsporozoite protein of the malaria parasite Plasmodium falciparum during sporogony in Anopheles stephensi midguts. Eur J Cell Biol. 1988;46(1):18–24. Epub 1988/04/01. pmid:3294006.
  29. 29. Lines JD, Wilkes TJ, Lyimo EO. Human malaria infectiousness measured by age-specific sporozoite rates in Anopheles gambiae in Tanzania. Parasitology. 1991;102 Pt 2:167–77. Epub 1991/04/01. pmid:1852484.
  30. 30. Mordecai EA, Paaijmans KP, Johnson LR, Balzer C, Ben-Horin T, de Moor E, et al. Optimal temperature for malaria transmission is dramatically lower than previously predicted. Ecol Lett. 2013;16(1):22–30. Epub 2012/10/12. pmid:23050931.
  31. 31. Hammond A, Galizi R, Kyrou K, Simoni A, Siniscalchi C, Katsanos D, et al. A CRISPR-Cas9 gene drive system targeting female reproduction in the malaria mosquito vector Anopheles gambiae. Nat Biotechnol. 2016;34(1):78–83. Epub 2015/12/08. pmid:26641531; PubMed Central PMCID: PMC4913862.
  32. 32. Kyrou K, Hammond AM, Galizi R, Kranjc N, Burt A, Beaghton AK, et al. A CRISPR-Cas9 gene drive targeting doublesex causes complete population suppression in caged Anopheles gambiae mosquitoes. Nat Biotechnol. 2018;36(11):1062–6. Epub 2018/09/25. pmid:30247490; PubMed Central PMCID: PMC6871539.
  33. 33. Thailayil J, Magnusson K, Godfray HC, Crisanti A, Catteruccia F. Spermless males elicit large-scale female responses to mating in the malaria mosquito Anopheles gambiae. Proc Natl Acad Sci U S A. 2011;108(33):13677–81. Epub 2011/08/10. pmid:21825136; PubMed Central PMCID: PMC3158155.
  34. 34. Emami SN, Ranford-Cartwright LC, Ferguson HM. The transmission potential of malaria-infected mosquitoes (An.gambiae-Keele, An.arabiensis-Ifakara) is altered by the vertebrate blood type they consume during parasite development. Sci Rep. 2017;7:40520. Epub 2017/01/18. pmid:28094293; PubMed Central PMCID: PMC5240107.
  35. 35. Olszewski KL, Llinas M. Central carbon metabolism of Plasmodium parasites. Mol Biochem Parasitol. 2011;175(2):95–103. Epub 2010/09/21. pmid:20849882; PubMed Central PMCID: PMC3004993.
  36. 36. Atella GC, Bittencourt-Cunha PR, Nunes RD, Shahabuddin M, Silva-Neto MA. The major insect lipoprotein is a lipid source to mosquito stages of malaria parasite. Acta Trop. 2009;109(2):159–62. Epub 2008/11/18. pmid:19013123.
  37. 37. Mi-Ichi F, Kano S, Mitamura T. Oleic acid is indispensable for intraerythrocytic proliferation of Plasmodium falciparum. Parasitology. 2007;134(Pt 12):1671–7. Epub 2007/07/06. pmid:17610764.
  38. 38. Itoe MA, Sampaio JL, Cabal GG, Real E, Zuzarte-Luis V, March S, et al. Host cell phosphatidylcholine is a key mediator of malaria parasite survival during liver stage infection. Cell Host Microbe. 2014;16(6):778–86. Epub 2014/12/17. pmid:25498345; PubMed Central PMCID: PMC4271766.
  39. 39. Brancucci NMB, Gerdt JP, Wang C, De Niz M, Philip N, Adapa SR, et al. Lysophosphatidylcholine Regulates Sexual Stage Differentiation in the Human Malaria Parasite Plasmodium falciparum. Cell. 2017;171(7):1532–44 e15. Epub 2017/11/14. pmid:29129376; PubMed Central PMCID: PMC5733390.
  40. 40. Rono MK, Whitten MM, Oulad-Abdelghani M, Levashina EA, Marois E. The major yolk protein vitellogenin interferes with the anti-plasmodium response in the malaria mosquito Anopheles gambiae. PLoS Biol. 2010;8(7):e1000434. Epub 2010/07/24. pmid:20652016; PubMed Central PMCID: PMC2907290.
  41. 41. Costa G, Gildenhard M, Eldering M, Lindquist RL, Hauser AE, Sauerwein R, et al. Non-competitive resource exploitation within mosquito shapes within-host malaria infectivity and virulence. Nat Commun. 2018;9(1):3474. Epub 2018/08/29. pmid:30150763; PubMed Central PMCID: PMC6110728.
  42. 42. Aleshnick M, Ganusov VV, Nasir G, Yenokyan G, Sinnis P. Experimental determination of the force of malaria infection reveals a non-linear relationship to mosquito sporozoite loads. PLoS Pathog. 2020;16(5):e1008181. Epub 2020/05/27. pmid:32453765; PubMed Central PMCID: PMC7295235.
  43. 43. Armstrong PM, Ehrlich HY, Magalhaes T, Miller MR, Conway PJ, Bransfield A, et al. Successive blood meals enhance virus dissemination within mosquitoes and increase transmission potential. Nat Microbiol. 2020;5(2):239–47. Epub 2019/12/11. pmid:31819213; PubMed Central PMCID: PMC7199921.
  44. 44. Serafim TD, Coutinho-Abreu IV, Oliveira F, Meneses C, Kamhawi S, Valenzuela JG. Sequential blood meals promote Leishmania replication and reverse metacyclogenesis augmenting vector infectivity. Nat Microbiol. 2018;3(5):548–55. Epub 2018/03/21. pmid:29556108; PubMed Central PMCID: PMC6007031.
  45. 45. Travi BL, Orihel TC. Development of Brugia malayi and Dirofilaria immitis in Aedes aegypti: effect of the host's nutrition. Trop Med Parasitol. 1987;38(1):19–22. Epub 1987/03/01. pmid:3602836.
  46. 46. Chandler LJ, Wasieloski LP, Blair CD, Beaty BJ. Analysis of La Crosse virus S-segment RNA and its positive-sense transcripts in persistently infected mosquito tissues. J Virol. 1996;70(12):8972–6. Epub 1996/12/01. pmid:8971026; PubMed Central PMCID: PMC190994.
  47. 47. Tusting LS, Bousema T, Smith DL, Drakeley C. Measuring changes in Plasmodium falciparum transmission: precision, accuracy and costs of metrics. Adv Parasitol. 2014;84:151–208. Epub 2014/02/01. pmid:24480314; PubMed Central PMCID: PMC4847140.
  48. 48. Beier JC, Killeen GF, Githure JI. Short report: entomologic inoculation rates and Plasmodium falciparum malaria prevalence in Africa. Am J Trop Med Hyg. 1999;61(1):109–13. Epub 1999/08/04. pmid:10432066.
  49. 49. Gupta S, Trenholme K, Anderson RM, Day KP. Antigenic diversity and the transmission dynamics of Plasmodium falciparum. Science. 1994;263(5149):961–3. Epub 1994/02/18. pmid:8310293.
  50. 50. Rowland M, Hemingway J. Changes in malathion resistance with age in Anopheles stephensi from Pakistan. Pesticide Biochemistry and Physiology. 1987;28(2):239–47.
  51. 51. Lines JD, Nassor NS. DDT resistance in Anopheles gambiae declines with mosquito age. Med Vet Entomol. 1991;5(3):261–5. Epub 1991/07/01. pmid:1768918.
  52. 52. Oliver SV, Brooke BD. The effect of multiple blood-feeding on the longevity and insecticide resistant phenotype in the major malaria vector Anopheles arabiensis (Diptera: Culicidae). Parasit Vectors. 2014;7:390. Epub 2014/08/26. pmid:25150975; PubMed Central PMCID: PMC4161849.
  53. 53. Bellan SE. The importance of age dependent mortality and the extrinsic incubation period in models of mosquito-borne disease transmission and control. PLoS One. 2010;5(4):e10165. Epub 2010/04/21. pmid:20405010; PubMed Central PMCID: PMC2854142.
  54. 54. Baldini F, Gabrieli P, South A, Valim C, Mancini F, Catteruccia F. The interaction between a sexually transferred steroid hormone and a female protein regulates oogenesis in the malaria mosquito Anopheles gambiae. PLoS Biol. 2013;11(10):e1001695. Epub 2013/11/10. pmid:24204210; PubMed Central PMCID: PMC3812110.
  55. 55. Blandin S, Shiao SH, Moita LF, Janse CJ, Waters AP, Kafatos FC, et al. Complement-like protein TEP1 is a determinant of vectorial capacity in the malaria vector Anopheles gambiae. Cell. 2004;116(5):661–70. Epub 2004/03/10. pmid:15006349.
  56. 56. Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, et al. Fiji: an open-source platform for biological-image analysis. Nat Methods. 2012;9(7):676–82. Epub 2012/06/30. pmid:22743772; PubMed Central PMCID: PMC3855844.
  57. 57. Abatzoglou JT, Dobrowski SZ, Parks SA, Hegewisch KC. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci Data. 2018;5:170191. Epub 2018/01/10. pmid:29313841; PubMed Central PMCID: PMC5759372.
  58. 58. Fick SE, Hijmans RJ. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology. 2017;37(12):4302–15.
  59. 59. Wiebe A, Longbottom J, Gleave K, Shearer FM, Sinka ME, Massey NC, et al. Geographical distributions of African malaria vector sibling species and evidence for insecticide resistance. Malar J. 2017;16(1):85. Epub 2017/02/22. pmid:28219387; PubMed Central PMCID: PMC5319841.
  60. 60.
  61. 61. Villena OC, Ryan SJ, Murdock CC, Johnson LR. Temperature impacts the transmission of malaria parasites by Anopheles gambiae and Anopheles stephensi mosquitoes. bioRxiv. 2020. p. 2020.07.08.194472.