An Overview of the Effects of Climate on

Malaria Transmission

Barbara Wendelberger

27 April 2010

Some Simplifications to MARA Anopheles gambiae s.l. Plasmodium falciparum. Independent analyses of rainfall and

temperature

Why Climate Mappings Fail Lack of data Use of crude geographic and climate iso-

lines No clear, reproducible numerical

definitions Prevents ability to compare data

Improvements Large global data sets

Up to 1.6 billion observations daily Climate data Population data Satellite imagery and topography

Geographical Information Systems (GIS) Advanced imaging software

Overlaying of varying levels of understanding Ex. Rainfall and temperature

Finding Stability Distributions

MARA Finding the limits of the

distribution of stable malaria areas

Based on temperature and rainfall data

R0 (vectorial capacity) Main component strongly

determined by climate Reproduction rate of malaria

parasite and mosquito vector

Modeling Problems Malaria is not definable:

in space because the edge of the distribution is indistinct

in time because both intensity and distribution wax and wane with natural periodicity of events

Logic Boolean Logic

Climate has only two states Suitable for transmission (1) Unsuitable for transmission (0)

Fuzzy Logic An extension of Boolean logic

Allows “fractions” Suitable (1) Semi-suitable (between 0 and 1) Unsuitable (0)

Transmission Areas Perennial: always able to sustain

transmission Seasonal: suitable for a short season each

year Epidemic: long-term variation in climate

renders suitable conditions irregularly Malaria-free: always unsuitable

*Long term monthly means exclude rare epidemic zones

A “fuzzy” model that demonstrates the different suitability zones

Temperature Effects Sporogonic duration (n)

n = DD _ T – Tmin

DD=degree days for parasite development (111) T=mean temperatureTmin=temperature at which parasite development ceases

(16 C)

Mosquito survival (p) p = e (-1/(-4.4+1.31T-0.03T^2)

Defined by Martens Assumes constant humidity

Temperature, p, and n

pn = percentage of vector cohort that survives the required temperature time period

ld = larval density

= 1 ___(0.00554T – 0.06737)

Temperature, p, and n

Rainfall Best studied when temperature is not

limiting No direct, predictable relationship between

rainfall and Anopheles gambiae s.l. Anopheles gambiae s.l. breed more prolifically in

temporary, turbid water bodies, such as those formed by rain

Impacts: Humidity Saturation deficit Temporary and permanent bodies of water

Sustainability

Temperature cut-off point between epidemic and no-malaria zone: 18ºC

22ºC allows stable transmission

The rainfall requirement for stable transmission is ~80mm/month for at least 5 months

Climate/Transmission RelevanceMore limiting variable used.

Climate Change and Health Research(NIH Portfolio Analysis-funded activities in 2008)

Number of studies in some way related to climate change

1,357

Number that directly relate to climate change 7

Number that examine how climate variables affect health

85

Climate is likely an important factor but is not explicitly addressed

706

NIH Studies Health:

Infectious diseases, respiratory diseases, asthma, heat stress, exposure to environmental toxins, trauma/injury, and cancers

Exposure pathways: Extreme weather, UV radiation, pollution, water-

borne, vector-borne, and zoonotic diseases

Study Types Laboratory experiments,

population studies, field ecology, and mathematical modeling

Deaths The WHO

160,000 deaths due to climate change in 2000 From malaria, malnutrition, diarrhea, flooding, and

heat waves

BUT: How does this compare to climate-related

deaths in other years? What is the error? Could this number be within

the range of the normal number expected?

NIH Initiatives The NIH is interested in studies that

directly examine climate impacts on human health.

Research needs to bridge the gap between global scale and micro studies.

Could Global Warming Increase Malaria Prevalence?

Optimum constant temperatures for adults and larvae: 23ºC to 24ºC

Development rates Increased development for both parasite and vector with

increased temperature Could increase it to the point of weakening the progeny

Density At 30ºC, when density increases, survival increases At 27ºC, when density increases, survival decreases

Current Predictions Based On Continuing change in global temperature

The present distribution of malaria parasites and their mosquito vectors

Warming Effects High Temperature

Increase Development rate to adulthood Frequency of blood-feeding Rate at which parasites are required Parasite incubation time

Decrease Adult mosquito survival

Thermodynamics

Negative Correlation Coefficients?Data

Dar es Salaam (Tanzania) Dodowa (Ghana)

-0.7 (mean max monthly temp/number of cases)

Could the Malaria Endemicity Center Move?

Multiple factors suggest yes Intrinsic optimum temperature model

Exhibits the effects on enzyme inactivation in relation to development

Co-evolution of vector and parasite (23ºC to 24ºC) Temperature and the sexual events of the

malaria parasite in the mosquito gut Relative transcription levels of rRNA involved

in sporogony The success of mosquito development from

aquatic to adult stage

The Bottom Line Climate is a complex variable

Study individual components Understand how they interact and affect each

other If temperatures continue to increase, then

the center of malaria endemicity will likely move to avoid temperatures that are too hot to encourage stable development Tropics are not equivalent to “hot

environments”

Research Sources Ahumada, J.A.,D. Lapointe, and M.D. Samuel. 2004. Modeling the Population

Dynamics of Culex quinquefasciatus (Diptera: Culicidae), along an Elevational Gradient in Hawaii. J. Med. Entomol. 41 (6):1157-1170.

Armstrong J.A., and W.R. Bransby-Williams. 1961. The Maintenance of a Colony of Anopheles gambiae With Observations on the Effects of Changes in Temperature. Bull. WHO 24, 427-435.

Craig, M.H., R.W. Snow, and D. le Seuer. A Climate-Based Distribution Model of Malaria Transmission in Sub-Saharan Africa. Parasitology Today, vol. 15, no. 3, 1999.

Hay, S.I., Snow, R.W. and Rogers, D.J. (1998) Prediction of malaria seasons in Kenya using multi-temporal meteorological satellite sensor data. Trans. R. Soc. Trop. Med. Hyg. 92, 12–20

Ikemoto, T. 2008. Tropical Malaria Does Not Mean Hot Environments. J. Med. Entomol. 45(6): 963Ð969

Lindsay, S.W. and Martens, W.J.M. (1998) Malaria in the African highlands: past, present and future. Bull. WHO 76, 33–45.

Lyimo, E.O., W. Takken, and J. C. Koella. 1992. Effect of rearing temperature and larval density on larval survival, age at pupation and adult size of Anopheles gambiae. Entomol. exp. appl. 63: 265-271.

Taylor, D. Trans-NIH group assesses response to climate change.

Special thanks to Derrick Parker for the variety of literature that he made available for my research.