Vector dynamics predicts transmission dynamics: a simple, realistic and sensible approach for measuring malaria endemicity

AbstractEntomological indicators such as vector density, distribution, biology and bionomics and their vectorial attributes are important parameters for measuring the pattern and intensity of malaria transmission. Although published articles provide evidence for the existence of associations between entomological indices and malaria transmission dynamics, none of them is able to establish a strong correlation. In order to address this issue, the present study aims to assess how malaria transmission is influenced and can be predicted by local major vector dynamics. We carried out an entomological assessment of major Anopheline vector abundance, habit/habitat, resting and feeding behavior, infectivity rates, and other entomological parameters. Results suggest that malaria transmission was correlated with a vector control intervention and non-intervention scenario in a high endemic region of Kalahandi district of Odisha, India. Amongst all indices, infective anthropophagic vectors established a strong positive correlation with malaria morbidity in comparison to infective or anthropophagic vector species during both the study periods. Though other entomological parameters influenced the transmission intensity, little quantifiable association was detected among study sites. This study provides strong baseline evidence of an association between entomological indices and malaria transmission dynamics, which could be used as an early warning system for outbreak prediction.

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Heterogeneous exposure and hotspots for malaria vectors at three study sites in Uganda

Gates Open Research ◽

10.12688/gatesopenres.12838.2 ◽

2018 ◽

Vol 2 ◽

pp. 32 ◽

Cited By ~ 8

Author(s):

Su Yun Kang ◽

Katherine E. Battle ◽

Harry S. Gibson ◽

Laura V. Cooper ◽

Kilama Maxwell ◽

...

Keyword(s):

Malaria Transmission ◽

Malaria Vector ◽

Malaria Control ◽

Negative Binomial ◽

Indoor Residual Spraying ◽

Housing Quality ◽

Environmental Covariates ◽

Vector Density ◽

Vector Abundance ◽

Study Sites

Background: Heterogeneity in malaria transmission has household, temporal, and spatial components. These factors are relevant for improving the efficiency of malaria control by targeting heterogeneity. To quantify variation, we analyzed mosquito counts from entomological surveillance conducted at three study sites in Uganda that varied in malaria transmission intensity. Mosquito biting or exposure is a risk factor for malaria transmission. Methods: Using a Bayesian zero-inflated negative binomial model, validated via a comprehensive simulation study, we quantified household differences in malaria vector density and examined its spatial distribution. We introduced a novel approach for identifying changes in vector abundance hotspots over time by computing the Getis-Ord statistic on ratios of household biting propensities for different scenarios. We also explored the association of household biting propensities with housing and environmental covariates. Results: In each site, there was evidence for hot and cold spots of vector abundance, and spatial patterns associated with urbanicity, elevation, or other environmental covariates. We found some differences in the hotspots in rainy vs. dry seasons or before vs. after the application of control interventions. Housing quality explained a portion of the variation among households in mosquito counts. Conclusion: This work provided an improved understanding of heterogeneity in malaria vector density at the three study sites in Uganda and offered a valuable opportunity for assessing whether interventions could be spatially targeted to be aimed at abundance hotspots which may increase malaria risk. Indoor residual spraying was shown to be a successful measure of vector control interventions in Tororo, Uganda. Cement walls, brick floors, closed eaves, screened airbricks, and tiled roofs were features of a house that had shown reduction of household biting propensity. Improvements in house quality should be recommended as a supplementary measure for malaria control reducing risk of infection.

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Effects of climate change on Plasmodium vivax malaria transmission dynamics: A mathematical modeling approach

Applied Mathematics and Computation ◽

10.1016/j.amc.2018.11.001 ◽

2019 ◽

Vol 347 ◽

pp. 616-630 ◽

Cited By ~ 4

Author(s):

Jung Eun Kim ◽

Yongin Choi ◽

Chang Hyeong Lee

Keyword(s):

Climate Change ◽

Mathematical Modeling ◽

Plasmodium Vivax ◽

Malaria Transmission ◽

Vivax Malaria ◽

Transmission Dynamics ◽

Modeling Approach ◽

Plasmodium Vivax Malaria

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Probable autochthonous introduced malaria cases in Italy in 2009–2011 and the risk of local vector-borne transmission

Eurosurveillance ◽

10.2807/ese.17.48.20325-en ◽

2012 ◽

Vol 17 (48) ◽

Author(s):

R Romi ◽

D Boccolini ◽

M Menegon ◽

G Rezza

Keyword(s):

Malaria Transmission ◽

Environmental Conditions ◽

Vivax Malaria ◽

Central Italy ◽

South Central ◽

Vector Abundance ◽

Plasmodium Vivax Malaria ◽

Local Vector ◽

Vector Borne ◽

Local Transmission

We describe two cases of probable autochthonous introduced Plasmodium vivax malaria that occurred in 2009 and 2011 in two sites of South-Central Italy. Although the sources of the infections were not detected, local transmission could not be disproved and therefore the cases were classified as autochthonous. Sporadic P. vivax cases transmitted by indigenous vectors may be considered possible in some areas of the country where vector abundance and environmental conditions are favourable to malaria transmission.

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Global Stability of Malaria Transmission Dynamics Model with Logistic Growth

Discrete Dynamics in Nature and Society ◽

10.1155/2018/5759834 ◽

2018 ◽

Vol 2018 ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Abadi Abay Gebremeskel

Keyword(s):

Sensitivity Analysis ◽

Global Stability ◽

Malaria Transmission ◽

Equilibrium Points ◽

Transmission Dynamics ◽

Logistic Growth ◽

Asymptotically Stable ◽

Dynamics Model ◽

Globally Asymptotically Stable ◽

The Impact

Mathematical models become an important and popular tools to understand the dynamics of the disease and give an insight to reduce the impact of malaria burden within the community. Thus, this paper aims to apply a mathematical model to study global stability of malaria transmission dynamics model with logistic growth. Analysis of the model applies scaling and sensitivity analysis and sensitivity analysis of the model applied to understand the important parameters in transmission and prevalence of malaria disease. We derive the equilibrium points of the model and investigated their stabilities. The results of our analysis have shown that if R0≤1, then the disease-free equilibrium is globally asymptotically stable, and the disease dies out; if R0>1, then the unique endemic equilibrium point is globally asymptotically stable and the disease persists within the population. Furthermore, numerical simulations in the application of the model showed the abrupt and periodic variations.

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