Effect of Different Relative Humidities and Temperatures on Egg‐Production and Longevity of Adults of <i>Anopheles (Myzomyia) pharoensis</i> Theob.<sup>1</sup>

Gaaboub, I. A.; El-Sawaf, S. K.; El-Latif, M. A. Abd

doi:10.1111/j.1439-0418.1971.tb02098.x

Cited by 13 publications

(14 citation statements)

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“…Temperatures in the approximate range of 21°-32°C and a relative humidity of at least 60% are most conducive to transmission [38]. Malaria vectors need to live at least 8 days in order to transmit malaria, and higher humidity increases both survival rate and activity rate [43, 44]. These relationships explain why Anopheles stephensi is more active and prefers feeding during the night when relative humidity is higher.…”

Section: Discussionmentioning

confidence: 99%

Population Density, Climate Variables and Poverty Synergistically Structure Spatial Risk in Urban Malaria in India

et al. 2016

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BackgroundThe world is rapidly becoming urban with the global population living in cities projected to double by 2050. This increase in urbanization poses new challenges for the spread and control of communicable diseases such as malaria. In particular, urban environments create highly heterogeneous socio-economic and environmental conditions that can affect the transmission of vector-borne diseases dependent on human water storage and waste water management. Interestingly India, as opposed to Africa, harbors a mosquito vector, Anopheles stephensi, which thrives in the man-made environments of cities and acts as the vector for both Plasmodium vivax and Plasmodium falciparum, making the malaria problem a truly urban phenomenon. Here we address the role and determinants of within-city spatial heterogeneity in the incidence patterns of vivax malaria, and then draw comparisons with results for falciparum malaria.Methodology/principal findingsStatistical analyses and a phenomenological transmission model are applied to an extensive spatio-temporal dataset on cases of Plasmodium vivax in the city of Ahmedabad (Gujarat, India) that spans 12 years monthly at the level of wards. A spatial pattern in malaria incidence is described that is largely stationary in time for this parasite. Malaria risk is then shown to be associated with socioeconomic indicators and environmental parameters, temperature and humidity. In a more dynamical perspective, an Inhomogeneous Markov Chain Model is used to predict vivax malaria risk. Models that account for climate factors, socioeconomic level and population size show the highest predictive skill. A comparison to the transmission dynamics of falciparum malaria reinforces the conclusion that the spatio-temporal patterns of risk are strongly driven by extrinsic factors.Conclusion/significanceClimate forcing and socio-economic heterogeneity act synergistically at local scales on the population dynamics of urban malaria in this city. The stationarity of malaria risk patterns provides a basis for more targeted intervention, such as vector control, based on transmission ‘hotspots’. This is especially relevant for P. vivax, a more resilient parasite than P. falciparum, due to its ability to relapse and the operational shortcomings of delivering a “radical cure”.

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Section: Discussionmentioning

confidence: 99%

Population Density, Climate Variables and Poverty Synergistically Structure Spatial Risk in Urban Malaria in India

et al. 2016

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“…All mosquito and parasite traits that are important for transmission and linked to metabolism, such as reproduction, development, survival, biting rate, and extrinsic incubation period, are temperature dependent with an intermediate thermal optimum [19–21]. Humidity is positively associated with mosquito survival because the high surface area to volume ratio of mosquitoes exposes them to desiccation [22,23]. Standing water from rainfall provides essential larval and pupal habitat for mosquitoes, but the relationship is complex because heavy rainfall can flush away breeding habitats [24–26] and water storage practices during drought can increase water availability, mosquito abundance, and contact between mosquitoes and people [27–29].…”

Section: Introductionmentioning

confidence: 99%

Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents

Caldwell

LaBeaud

Lambin

et al. 2020

Preprint

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47Climate drives population dynamics, but when the underlying mechanisms are 48 unresolved, studies can lead to seemingly contradictory effects of climate on natural 49 populations. Climate-sensitive vector-borne diseases such as dengue, chikungunya, and 50Zika are one example where climate appears to have opposing effects in different 51 contexts. In this study, we use a mathematical model to directly connect climate-driven 52 mosquito physiology measured in laboratory studies to observed vector and disease 53 dynamics in the field across ecologically and culturally distinct settings in Ecuador and 54Kenya. We show that temperature, rainfall, and humidity predict Aedes aepgyti 55 abundances and laboratory-confirmed arboviral incidence across ecologically distinct 56 settings. Further, this trait-based approach resolves seemingly contradictory results from 57 prior field studies and highlights climate conditions where mechanisms remain 58 unresolved. Using this mechanistic model, we tested several intervention strategies and 59 found that reducing immature mosquito habitat or contact rate between mosquitoes and 60 humans are more effective interventions than killing adult mosquitoes. These results can 61 help guide intervention efforts and improve climate change predictions for vector-borne 62 diseases. 63 64 Introduction: 65Climate is a major driver of species interactions and population dynamics, but the 66 mechanisms underlying these relationships are often poorly understood and rarely tested 67 in the field [1]. One of the primary ways that climate impacts populations is through its 68 effects on species' vital rates [2]. However, these mechanistic effects can lead to 69 seemingly contradictory results in the field because multiple climate variables may act 70 synergistically, with each climate variable potentially affecting multiple vital rates, and 71 their impacts may be nonlinear, changing direction and relative importance across a 72 gradient of conditions. Vector-borne diseases provide an interesting case study to test 73 whether climate sensitive traits measured in controlled, laboratory settings can reconcile 74 seemingly contradictory results from field studies. For example, mosquito-borne 75 arboviral diseases such as dengue, chikungunya, and Zika are clearly climate-sensitive: a 76 body of field research has consistently identified temperature, rainfall, and humidity as 77 important predictors of disease, but sometimes with opposite conclusions about the 78 magnitude and direction of effects of climate on mosquito and disease dynamics [3][4][5][6][7][8]. 79For example, dengue incidence correlated with temperature positively in Mexico [9] but 80 negatively in Thailand [10]. We hypothesize that such opposing effects could be 81 simultaneously correct if disease dynamics are context-dependent or nonlinear, and each 82 model describes true disease dynamics but only within a small subset of conditions (e.g., 83 specific locations or seasons). 84 85 Understanding the mechanisms that drive disease dynamic...

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“…Mosquitoes do not escape this rule. [8] compared to a given temperature, the survival of female anopheles pharoensis at 20 • , 26 • , 30 • C and a slight difference in terms of longevity in conditions of relative humidity taken between 50% and 90%. Whereas the probability of survival was independent of age, [9] measured the longevity of Anopheles gambiae s.s by considering the relative humidity at 40%, 60%, 80% and 100%, and a temperature between 5 • C and 40 • C. There is a slight difference in survival with a relative humidity between 60% and 100%.…”

Section: Surveymentioning

confidence: 99%

Meta-Population Modelling and Simulation of the Dynamic of Malaria Transmission with Influence of Climatic Factors

Noubissi¹,

Kamgang²,

Ramat³

et al. 2017

IJITCS

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We model the dynamic of malaria transmission taking into account climatic factors and the migration between Douala and Yaoundé , Yaoundé and Ngaoundé ré , three cities of Cameroon country. We show how variations of climatic factors such as temperature and relative humidity affect the malaria spread. We propose a meta-population model of the dynamic transmission of malaria that evolves in space and time and that takes into account temperature and relative humidity and the migration between Douala and Yaoundé , Yaoundé and Ngaoundé ré . More, we integrate the variation of environmental factors as events also called mathematical impulsion that can disrupt the model evolution at any time. Our modelling has been done using the Discrete EVents System Specification (DEVS) formalism. Our implementation has been done on Virtual Laboratory Environment (VLE) that uses DEVS formalism and abstract simulators for coupling models by integrating the concept of DEVS.

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Effect of Different Relative Humidities and Temperatures on Egg‐Production and Longevity of Adults of Anopheles (Myzomyia) pharoensis Theob.¹

Cited by 13 publications

References 4 publications

Population Density, Climate Variables and Poverty Synergistically Structure Spatial Risk in Urban Malaria in India

Population Density, Climate Variables and Poverty Synergistically Structure Spatial Risk in Urban Malaria in India

Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents

Meta-Population Modelling and Simulation of the Dynamic of Malaria Transmission with Influence of Climatic Factors

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Effect of Different Relative Humidities and Temperatures on Egg‐Production and Longevity of Adults of Anopheles (Myzomyia) pharoensis Theob.1

Cited by 13 publications

References 4 publications

Population Density, Climate Variables and Poverty Synergistically Structure Spatial Risk in Urban Malaria in India

Population Density, Climate Variables and Poverty Synergistically Structure Spatial Risk in Urban Malaria in India

Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents

Meta-Population Modelling and Simulation of the Dynamic of Malaria Transmission with Influence of Climatic Factors

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Effect of Different Relative Humidities and Temperatures on Egg‐Production and Longevity of Adults of Anopheles (Myzomyia) pharoensis Theob.¹