This site needs JavaScript to work properly. Please enable it to take advantage of the complete set of features!
Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation

Save citation to file

Add to Collections

Name must be less than 100 characters
Unable to load your collection due to an error
Please try again

Add to My Bibliography

Unable to load your delegates due to an error
Please try again

Your saved search

Would you like email updates of new search results?
Saved Search Alert Radio Buttons
()

Create a file for external citation management software

Your RSS Feed

. 2017 Oct 16;15(10):e2003489.
doi: 10.1371/journal.pbio.2003489. eCollection 2017 Oct.

Quantifying the effects of temperature on mosquito and parasite traits that determine the transmission potential of human malaria

Affiliations

Affiliation

  • 1 The Pennsylvania State University Department of Entomology and Center for Infectious Disease Dynamics, University Park, Pennsylvania, United States of America.

Quantifying the effects of temperature on mosquito and parasite traits that determine the transmission potential of human malaria

Lillian L M Shapiro et al. PLoS Biol. .
. 2017 Oct 16;15(10):e2003489.
doi: 10.1371/journal.pbio.2003489. eCollection 2017 Oct.

Affiliation

  • 1 The Pennsylvania State University Department of Entomology and Center for Infectious Disease Dynamics, University Park, Pennsylvania, United States of America.

Abstract

Malaria transmission is known to be strongly impacted by temperature. The current understanding of how temperature affects mosquito and parasite life history traits derives from a limited number of empirical studies. These studies, some dating back to the early part of last century, are often poorly controlled, have limited replication, explore a narrow range of temperatures, and use a mixture of parasite and mosquito species. Here, we use a single pairing of the Asian mosquito vector, An. stephensi and the human malaria parasite, P. falciparum to conduct a comprehensive evaluation of the thermal performance curves of a range of mosquito and parasite traits relevant to transmission. We show that biting rate, adult mortality rate, parasite development rate, and vector competence are temperature sensitive. Importantly, we find qualitative and quantitative differences to the assumed temperature-dependent relationships. To explore the overall implications of temperature for transmission, we first use a standard model of relative vectorial capacity. This approach suggests a temperature optimum for transmission of 29°C, with minimum and maximum temperatures of 12°C and 38°C, respectively. However, the robustness of the vectorial capacity approach is challenged by the fact that the empirical data violate several of the model's simplifying assumptions. Accordingly, we present an alternative model of relative force of infection that better captures the observed biology of the vector-parasite interaction. This model suggests a temperature optimum for transmission of 26°C, with a minimum and maximum of 17°C and 35°C, respectively. The differences between the models lead to potentially divergent predictions for the potential impacts of current and future climate change on malaria transmission. The study provides a framework for more detailed, system-specific studies that are essential to develop an improved understanding on the effects of temperature on malaria transmission.

PubMed Disclaimer

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1

Fig 1. Gompertz model predictions for each…

Fig 1. Gompertz model predictions for each temperature and block combination overlaid on corresponding raw…

Fig 1. Gompertz model predictions for each temperature and block combination overlaid on corresponding raw (Kaplan-Meier) survival data; (A) experimental block 1; (B) experimental block 2.
Raw data and numerical values can be accessed at http://dx.doi.org/10.5061/dryad.74389 [34].
Fig 2

Fig 2. Dynamics of infectiousness over time…

Fig 2. Dynamics of infectiousness over time for each temperature and block combination.

Sporogony represented…

Fig 2. Dynamics of infectiousness over time for each temperature and block combination.
Sporogony represented by the change in proportion of infectious mosquitoes over time. Blue points with connecting lines represent dynamics for each experimental cup in block 1; red points with connecting lines represent cup dynamics for block 2. The logistic regression model for block 1 is depicted by the solid black line, whereas the model for block 2 is the dashed black line. Raw data and numerical values can be accessed at http://dx.doi.org/10.5061/dryad.74389 [34].
Fig 3

Fig 3

Predicted values for EIP 10

Fig 3

Predicted values for EIP 10 (light grey), EIP 50 (grey), and EIP 90

Fig 3
Predicted values for EIP10 (light grey), EIP50 (grey), and EIP90 (black) for each temperature in (A) experimental block 1 and (B) experimental block 2; dotted lines represent the predicted thermal performance curve for the respective EIPs, while the red line is the EIP of P. falciparum predicted from the widely-used degree-day model of Detinova 1962 [27]. (C) Predicted values for vector competence (g, the asymptote of the sporogony curve in Fig 2) across temperature for block 1 (blue) and block 2 (red). Error bars represent 95% confidence intervals. Numerical values can be accessed at http://dx.doi.org/10.5061/dryad.74389 [34]. EIP, extrinsic incubation period.
Fig 4

Fig 4. Mean length of the gonotrophic…

Fig 4. Mean length of the gonotrophic cycle (days) for each temperature.

Error bars represent…

Fig 4. Mean length of the gonotrophic cycle (days) for each temperature.
Error bars represent standard deviation; superscripts represent significant differences (p < 0.05) upon posthoc analysis. Numerical values can be accessed at http://dx.doi.org/10.5061/dryad.74389 [34].
Fig 5

Fig 5

Thermal performance curves for (A)…

Fig 5

Thermal performance curves for (A) biting rate, (B) vector competence, (C) mosquito mortality…

Fig 5
Thermal performance curves for (A) biting rate, (B) vector competence, (C) mosquito mortality rate, and (D) parasite development rate (based on the extrinsic incubation period time in days until 50% of maximum infectiousness [EIP50]), comparing the current study to the equivalent curves proposed by Mordecai et al. [4] by using mixed-species data. (E) Shows the predicted temperature-dependent model of rVC based on the thermal performance curves from this study, using data for the EIP50. Numerical values can be accessed at http://dx.doi.org/10.5061/dryad.74389 [34]. EIP, extrinsic incubation period; rVC, relative vectorial capacity.
Fig 6

Fig 6. Curves for dynamic model of…

Fig 6. Curves for dynamic model of transmission potential for each temperature.

Area curves for…

Fig 6. Curves for dynamic model of transmission potential for each temperature.
Area curves for rates of survival (blue) and infection (pink) for each temperature; pPurple areas represent the product of the two 2 curves (i.e., the number of mosquitoes alive and infectious or “infectious mosquito days”). Dashed line represents the day at which collection of raw data ended; curves to the right of the dashed line represent values calculated from both survival and infection model estimates (mean for both experimental blocks). Numerical values can be accessed at http://dx.doi.org/10.5061/dryad.74389 [34].
Fig 7

Fig 7

(A) Best fit thermal performance…

Fig 7

(A) Best fit thermal performance curve for relative force of infection (here the…

Fig 7
(A) Best fit thermal performance curve for relative force of infection (here the number of infectious bites predicted for a cohort of 100 female mosquitoes); grey points represent the calculated number of bites for the mean of both experimental blocks and error bars represent standard deviation. (B) Comparison of scaled thermal performance curves for rVC and relative force of infection. Numerical values can be accessed at http://dx.doi.org/10.5061/dryad.74389 [34]. rVC, relative vectorial capacity.

References

    1. Paaijmans KP, Blanford S, Chan BHK, Thomas MB. Warmer temperatures reduce the vectorial capacity of malaria mosquitoes. Biol Lett. 2012;8: 465–8. doi: 10.1098/rsbl.2011.1075 - DOI - PMC - PubMed
    1. 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: 15135–9. doi: 10.1073/pnas.1006422107 - DOI - PMC - PubMed
    1. Okech BA, Gouagna LC, Walczak E, Kabiru EW, Beier JC, Yan G, et al. The development of Plasmodium falciparum in experimentally infected Anopheles gambiae (Diptera: Culicidae) under ambient microhabitat temperature in western Kenya. Acta Trop. 2004;92: 99–108. doi: 10.1016/j.actatropica.2004.06.003 - DOI - PubMed
    1. 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: 22–30. doi: 10.1111/ele.12015 - DOI - PubMed
    1. Alonso D, Bouma MJ, Pascual M. Epidemic malaria and warmer temperatures in recent decades in an East African highland. Proc R Soc B Biol Sci. 2011;278: 1661–1669. doi: 10.1098/rspb.2010.2020 - DOI - PMC - PubMed
Cite
Morty Proxy This is a proxified and sanitized view of the page, visit original site.