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Mazarire TT, Lobb L, Newete SW, Munhenga G. The Impact of Climatic Factors on Temporal Mosquito Distribution and Population Dynamics in an Area Targeted for Sterile Insect Technique Pilot Trials. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2024; 21:558. [PMID: 38791773 PMCID: PMC11121319 DOI: 10.3390/ijerph21050558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 04/20/2024] [Accepted: 04/24/2024] [Indexed: 05/26/2024]
Abstract
It is widely accepted that climate affects the mosquito life history traits; however, its precise role in determining mosquito distribution and population dynamics is not fully understood. This study aimed to investigate the influence of various climatic factors on the temporal distribution of Anopheles arabiensis populations in Mamfene, South Africa between 2014 and 2019. Time series analysis, wavelet analysis, cross-correlation analysis, and regression model combined with the autoregressive integrated moving average (ARIMA) model were utilized to assess the relationship between climatic factors and An. arabiensis population density. In total 3826 adult An. arabiensis collected was used for the analysis. ARIMA (0, 1, 2) (0, 0, 1)12 models closely described the trends observed in An. arabiensis population density and distribution. The wavelet coherence and time-lagged correlation analysis showed positive correlations between An. arabiensis population density and temperature (r = 0.537 ), humidity (r = 0.495) and rainfall (r = 0.298) whilst wind showed negative correlations (r = -0.466). The regression model showed that temperature (p = 0.00119), rainfall (p = 0.0436), and humidity (p = 0.0441) as significant predictors for forecasting An. arabiensis abundance. The extended ARIMA model (AIC = 102.08) was a better fit for predicting An. arabiensis abundance compared to the basic model. Anopheles arabiensis still remains the predominant malaria vector in the study area and climate variables were found to have varying effects on the distribution and abundance of An. arabiensis. This necessitates other complementary vector control strategies such as the Sterile Insect Technique (SIT) which involves releasing sterile males into the environment to reduce mosquito populations. This requires timely mosquito and climate information to precisely target releases and enhance the effectiveness of the program, consequently reducing the malaria risk.
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Affiliation(s)
- Theresa Taona Mazarire
- Centre for Emerging Zoonotic and Parasitic Diseases, National Institute for Communicable Diseases, National Health Laboratory Service, Johannesburg 2131, South Africa; (L.L.); (G.M.)
- Wits Research Institute for Malaria, School of Pathology, University of the Witwatersrand, Johannesburg 2050, South Africa
- Geoinformatics Division, Agricultural Research Council-Natural Resource and Engineering, Arcadia, Pretoria 0083, South Africa;
| | - Leanne Lobb
- Centre for Emerging Zoonotic and Parasitic Diseases, National Institute for Communicable Diseases, National Health Laboratory Service, Johannesburg 2131, South Africa; (L.L.); (G.M.)
| | - Solomon Wakshom Newete
- Geoinformatics Division, Agricultural Research Council-Natural Resource and Engineering, Arcadia, Pretoria 0083, South Africa;
- School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Bramfontein, Johannesburg 2050, South Africa
| | - Givemore Munhenga
- Centre for Emerging Zoonotic and Parasitic Diseases, National Institute for Communicable Diseases, National Health Laboratory Service, Johannesburg 2131, South Africa; (L.L.); (G.M.)
- Wits Research Institute for Malaria, School of Pathology, University of the Witwatersrand, Johannesburg 2050, South Africa
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Mwima R, Hui TYJ, Nanteza A, Burt A, Kayondo JK. Potential persistence mechanisms of the major Anopheles gambiae species complex malaria vectors in sub-Saharan Africa: a narrative review. Malar J 2023; 22:336. [PMID: 37936194 PMCID: PMC10631165 DOI: 10.1186/s12936-023-04775-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 10/30/2023] [Indexed: 11/09/2023] Open
Abstract
The source of malaria vector populations that re-establish at the beginning of the rainy season is still unclear yet knowledge of mosquito behaviour is required to effectively institute control measures. Alternative hypotheses like aestivation, local refugia, migration between neighbouring sites, and long-distance migration (LDM) are stipulated to support mosquito persistence. This work assessed the malaria vector persistence dynamics and examined various studies done on vector survival via these hypotheses; aestivation, local refugia, local or long-distance migration across sub-Saharan Africa, explored a range of methods used, ecological parameters and highlighted the knowledge trends and gaps. The results about a particular persistence mechanism that supports the re-establishment of Anopheles gambiae, Anopheles coluzzii or Anopheles arabiensis in sub-Saharan Africa were not conclusive given that each method used had its limitations. For example, the Mark-Release-Recapture (MRR) method whose challenge is a low recapture rate that affects its accuracy, and the use of time series analysis through field collections whose challenge is the uncertainty about whether not finding mosquitoes during the dry season is a weakness of the conventional sampling methods used or because of hidden shelters. This, therefore, calls for further investigations emphasizing the use of ecological experiments under controlled conditions in the laboratory or semi-field, and genetic approaches, as they are known to complement each other. This review, therefore, unveils and assesses the uncertainties that influence the different malaria vector persistence mechanisms and provides recommendations for future studies.
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Affiliation(s)
- Rita Mwima
- Department of Entomology, Uganda Virus Research Institute (UVRI), Entebbe, Uganda
- Department of Biotechnical and Diagnostic Sciences, College of Veterinary Medicine, Animal Resources and Biosecurity (COVAB), Makerere University, Kampala, Uganda
| | - Tin-Yu J Hui
- Silwood Park Campus, Department of Life Sciences, Imperial College London, Ascot, UK
| | - Ann Nanteza
- Department of Biotechnical and Diagnostic Sciences, College of Veterinary Medicine, Animal Resources and Biosecurity (COVAB), Makerere University, Kampala, Uganda
| | - Austin Burt
- Silwood Park Campus, Department of Life Sciences, Imperial College London, Ascot, UK
| | - Jonathan K Kayondo
- Department of Entomology, Uganda Virus Research Institute (UVRI), Entebbe, Uganda.
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Gonzalez-Daza W, Vivero-Gómez RJ, Altamiranda-Saavedra M, Muylaert RL, Landeiro VL. Time lag effect on malaria transmission dynamics in an Amazonian Colombian municipality and importance for early warning systems. Sci Rep 2023; 13:18636. [PMID: 37903862 PMCID: PMC10616112 DOI: 10.1038/s41598-023-44821-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 10/12/2023] [Indexed: 11/01/2023] Open
Abstract
Malaria remains a significant public health problem worldwide, particularly in low-income regions with limited access to healthcare. Despite the use of antimalarial drugs, transmission remains an issue in Colombia, especially among indigenous populations in remote areas. In this study, we used an SIR Ross MacDonald model that considered land use change, temperature, and precipitation to analyze eco epidemiological parameters and the impact of time lags on malaria transmission in La Pedrera-Amazonas municipality. We found changes in land use between 2007 and 2020, with increases in forested areas, urban infrastructure and water edges resulting in a constant increase in mosquito carrying capacity. Temperature and precipitation variables exhibited a fluctuating pattern that corresponded to rainy and dry seasons, respectively and a marked influence of the El Niño climatic phenomenon. Our findings suggest that elevated precipitation and temperature increase malaria infection risk in the following 2 months. The risk is influenced by the secondary vegetation and urban infrastructure near primary forest formation or water body edges. These results may help public health officials and policymakers develop effective malaria control strategies by monitoring precipitation, temperature, and land use variables to flag high-risk areas and critical periods, considering the time lag effect.
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Affiliation(s)
- William Gonzalez-Daza
- Programa do Pós-Graduação em Ecologia e Conservação da Biodiversidade, Departamento de Biociências, Universidade Federal de Mato Grosso, Cuiabá, MT, 78060-900, Brazil.
| | - Rafael Jose Vivero-Gómez
- Grupo de Microbiodiversidad y Bioprospección, Laboratorio de Biología Celular y Molecular, Universidad Nacional de Colombia Sede Medellín, Street 59A #63-20, 050003, Medellín, Colombia
- Programa de Estudio y Control de Enfermedades Tropicales-PECET, Universidad de Antioquia, Calle 62 No. 52-59 Laboratorio 632, Medellín, Colombia
| | | | - Renata L Muylaert
- Molecular Epidemiology and Public Health Laboratory, School of Veterinary Science, Massey University, Palmerston North, New Zealand
| | - Victor Lemes Landeiro
- Departamento de Botânica e Ecologia, Instituto de Biociências, Universidade Federal de Mato Grosso, Cuiabá, MT, 78060-900, Brazil
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Ryan SJ, Lippi CA, Caplan T, Diaz A, Dunbar W, Grover S, Johnson S, Knowles R, Lowe R, Mateen BA, Thomson MC, Stewart-Ibarra AM. The current landscape of software tools for the climate-sensitive infectious disease modelling community. Lancet Planet Health 2023; 7:e527-e536. [PMID: 37286249 DOI: 10.1016/s2542-5196(23)00056-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 03/15/2023] [Accepted: 03/16/2023] [Indexed: 06/09/2023]
Abstract
Climate-sensitive infectious disease modelling is crucial for public health planning and is underpinned by a complex network of software tools. We identified only 37 tools that incorporated both climate inputs and epidemiological information to produce an output of disease risk in one package, were transparently described and validated, were named (for future searching and versioning), and were accessible (ie, the code was published during the past 10 years or was available on a repository, web platform, or other user interface). We noted disproportionate representation of developers based at North American and European institutions. Most tools (n=30 [81%]) focused on vector-borne diseases, and more than half (n=16 [53%]) of these tools focused on malaria. Few tools (n=4 [11%]) focused on food-borne, respiratory, or water-borne diseases. The under-representation of tools for estimating outbreaks of directly transmitted diseases represents a major knowledge gap. Just over half (n=20 [54%]) of the tools assessed were described as operationalised, with many freely available online.
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Affiliation(s)
- Sadie J Ryan
- Quantitative Disease Ecology and Conservation Laboratory Group, Department of Geography, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.
| | - Catherine A Lippi
- Quantitative Disease Ecology and Conservation Laboratory Group, Department of Geography, University of Florida, Gainesville, FL, USA; Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | | | - Avriel Diaz
- Department of Earth and Environmental Sciences, Columbia University, New York, NY, USA
| | - Willy Dunbar
- National Collaborating Centre for Healthy Public Policy, Montreal, QC, Canada
| | | | | | | | - Rachel Lowe
- Barcelona Supercomputing Center, Barcelona, Spain; Catalan Institution for Research and Advanced Studies, Barcelona, Spain; Centre on Climate Change & Planetary Health and Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK
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Yamba EI, Fink AH, Badu K, Asare EO, Tompkins AM, Amekudzi LK. Climate Drivers of Malaria Transmission Seasonality and Their Relative Importance in Sub-Saharan Africa. GEOHEALTH 2023; 7:e2022GH000698. [PMID: 36743738 PMCID: PMC9884660 DOI: 10.1029/2022gh000698] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 12/15/2022] [Accepted: 01/11/2023] [Indexed: 06/18/2023]
Abstract
A new database of the Entomological Inoculation Rate (EIR) was used to directly link the risk of infectious mosquito bites to climate in Sub-Saharan Africa. Applying a statistical mixed model framework to high-quality monthly EIR measurements collected from field campaigns in Sub-Saharan Africa, we analyzed the impact of rainfall and temperature seasonality on EIR seasonality and determined important climate drivers of malaria seasonality across varied climate settings in the region. We observed that seasonal malaria transmission was within a temperature window of 15°C-40°C and was sustained if average temperature was well above 15°C or below 40°C. Monthly maximum rainfall for seasonal malaria transmission did not exceed 600 in west Central Africa, and 400 mm in the Sahel, Guinea Savannah, and East Africa. Based on a multi-regression model approach, rainfall and temperature seasonality were found to be significantly associated with malaria seasonality in all parts of Sub-Saharan Africa except in west Central Africa. Topography was found to have significant influence on which climate variable is an important determinant of malaria seasonality in East Africa. Seasonal malaria transmission onset lags behind rainfall only at markedly seasonal rainfall areas such as Sahel and East Africa; elsewhere, malaria transmission is year-round. High-quality EIR measurements can usefully supplement established metrics for seasonal malaria. The study's outcome is important for the improvement and validation of weather-driven dynamical mathematical malaria models that directly simulate EIR. Our results can contribute to the development of fit-for-purpose weather-driven malaria models to support health decision-making in the fight to control or eliminate malaria in Sub-Saharan Africa.
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Affiliation(s)
- Edmund I. Yamba
- Department of Meteorology and Climate ScienceKwame Nkrumah University of Science and Technology (KNUST)KumasiGhana
| | - Andreas H. Fink
- Institute of Meteorology and Climate ResearchKarlsruhe Institute of TechnologyKarlsruheGermany
| | - Kingsley Badu
- Department of Theoretical and Applied BiologyKwame Nkrumah University of Science and TechnologyKumasiGhana
| | - Ernest O. Asare
- Department of Epidemiology of Microbial DiseasesYale School of Public HealthYale UniversityNew HavenCTUSA
| | - Adrian M. Tompkins
- International Centre for Theoretical Physics, Earth System PhysicsTriesteItaly
| | - Leonard K. Amekudzi
- Department of Meteorology and Climate ScienceKwame Nkrumah University of Science and Technology (KNUST)KumasiGhana
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Lacroux C, Pouydebat E, Rossignol M, Durand S, Aleeje A, Asalu E, Chandre F, Krief S. Repellent activity against Anopheles gambiae of the leaves of nesting trees in the Sebitoli chimpanzee community of Kibale National Park, Uganda. Malar J 2022; 21:271. [PMID: 36163024 PMCID: PMC9513939 DOI: 10.1186/s12936-022-04291-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 09/09/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Every evening, chimpanzees (Pan troglodytes) build a sleeping platform so called "nest" by intertwining branches of tree. Most of chimpanzees' communities studied have a preference for tree species in which they nest. As female mosquitoes are feeding on the blood of their host at nighttime, chimpanzees may prevent being disturbed and bitten by mosquitoes by selecting tree species having properties to repel them. METHODS To test the hypothesis that chimpanzees choose tree species for their aromatic properties, data related to 1,081 nesting trees built between 2017 and 2019 in the Sebitoli community of Kibale National Park (Uganda) were analysed. The 10 most used trees were compared to the 10 most common trees in the habitat that were not preferred for nesting. Leaves from the 20 trees species were collected and hydro-distillated to obtain essential oils and one of the by-products for behavioural bioassays against females of the African mosquito, Anopheles gambiae. RESULTS Sebitoli chimpanzees showed tree preferences: 10 species correspond to more than 80% of the nesting trees. Out of the essential oil obtained from the 10 nesting trees, 7 extracts for at least one concentration tested showed spatial repellency, 7 were irritant by contact and none were toxic. In the other hand, for the abundant trees in their habitat not used by chimpanzees, only 3 were repellent and 5 irritants. DISCUSSION AND CONCLUSION This study contributes to evidence that chimpanzees, to avoid annoying mosquitoes, may select their nesting trees according to their repellent properties (linked to chemical parameters), a potential inspiration for human health.
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Affiliation(s)
- Camille Lacroux
- UMR 7206 CNRS/MNHN/P7, Eco-Anthropologie, Museum National d'Histoire Naturelle, Musée de L'Homme, 17 place du Trocadéro, 75116, Paris, France. .,UMR 7179 CNRS/MNHN, Mécanismes Adaptatifs Et Evolution, Museum National d'Histoire Naturelle, 57 rue Cuvier, 75231, Paris, France. .,Sebitoli Chimpanzee Project, Great Apes Conservation Project, Kibale National Park, Fort Portal, Uganda. .,La Phocéenne de Cosmétique, ZA Les Roquassiers, 174 Rue de la Forge, 13300, Salon-de-Provence, France.
| | - Emmanuelle Pouydebat
- UMR 7179 CNRS/MNHN, Mécanismes Adaptatifs Et Evolution, Museum National d'Histoire Naturelle, 57 rue Cuvier, 75231, Paris, France
| | - Marie Rossignol
- Maladies Infectieuses et Vecteurs: Ecologie, Génétique, Evolution Et Contrôle, Institut de Recherche Et Développement, UMR MIVEGEC IRD/CNRS/Montpellier University, 911 avenue Agropolis, 34394, Montpellier Cedex 5, France
| | - Sophie Durand
- La Phocéenne de Cosmétique, ZA Les Roquassiers, 174 Rue de la Forge, 13300, Salon-de-Provence, France
| | - Alfred Aleeje
- Sebitoli Chimpanzee Project, Great Apes Conservation Project, Kibale National Park, Fort Portal, Uganda
| | - Edward Asalu
- Uganda Wildlife Authority, Kibale National Park, Fort Portal, Uganda
| | - Fabrice Chandre
- Maladies Infectieuses et Vecteurs: Ecologie, Génétique, Evolution Et Contrôle, Institut de Recherche Et Développement, UMR MIVEGEC IRD/CNRS/Montpellier University, 911 avenue Agropolis, 34394, Montpellier Cedex 5, France
| | - Sabrina Krief
- UMR 7206 CNRS/MNHN/P7, Eco-Anthropologie, Museum National d'Histoire Naturelle, Musée de L'Homme, 17 place du Trocadéro, 75116, Paris, France.,Sebitoli Chimpanzee Project, Great Apes Conservation Project, Kibale National Park, Fort Portal, Uganda
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Erguler K, Mendel J, Petrić DV, Petrić M, Kavran M, Demirok MC, Gunay F, Georgiades P, Alten B, Lelieveld J. A dynamically structured matrix population model for insect life histories observed under variable environmental conditions. Sci Rep 2022; 12:11587. [PMID: 35804074 PMCID: PMC9270365 DOI: 10.1038/s41598-022-15806-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 06/29/2022] [Indexed: 11/09/2022] Open
Abstract
Various environmental drivers influence life processes of insect vectors that transmit human disease. Life histories observed under experimental conditions can reveal such complex links; however, designing informative experiments for insects is challenging. Furthermore, inferences obtained under controlled conditions often extrapolate poorly to field conditions. Here, we introduce a pseudo-stage-structured population dynamics model to describe insect development as a renewal process with variable rates. The model permits representing realistic life stage durations under constant and variable environmental conditions. Using the model, we demonstrate how random environmental variations result in fluctuating development rates and affect stage duration. We apply the model to infer environmental dependencies from the life history observations of two common disease vectors, the southern (Culex quinquefasciatus) and northern (Culex pipiens) house mosquito. We identify photoperiod, in addition to temperature, as pivotal in regulating larva stage duration, and find that carefully timed life history observations under semi-field conditions accurately predict insect development throughout the year. The approach we describe augments existing methods of life table design and analysis, and contributes to the development of large-scale climate- and environment-driven population dynamics models for important disease vectors.
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Affiliation(s)
- Kamil Erguler
- The Cyprus Institute, Climate and Atmosphere Research Centre (CARE-C), 20 Konstantinou Kavafi Street, 2121, Aglantzia, Nicosia, Cyprus.
| | - Jacob Mendel
- Department of Medical Sciences, University of Oxford, Oxford, UK
| | - Dušan Veljko Petrić
- Laboratory for Medical and Veterinary Entomology, Faculty of Agriculture, University of Novi Sad, 21000, Novi Sad, Serbia
| | | | - Mihaela Kavran
- Laboratory for Medical and Veterinary Entomology, Faculty of Agriculture, University of Novi Sad, 21000, Novi Sad, Serbia
| | - Murat Can Demirok
- Biology Department, Ecology Division, VERG Laboratories, Faculty of Science, Hacettepe University, 06800, Beytepe-Ankara, Turkey
| | - Filiz Gunay
- Biology Department, Ecology Division, VERG Laboratories, Faculty of Science, Hacettepe University, 06800, Beytepe-Ankara, Turkey
| | - Pantelis Georgiades
- The Cyprus Institute, Climate and Atmosphere Research Centre (CARE-C), 20 Konstantinou Kavafi Street, 2121, Aglantzia, Nicosia, Cyprus
| | - Bulent Alten
- Biology Department, Ecology Division, VERG Laboratories, Faculty of Science, Hacettepe University, 06800, Beytepe-Ankara, Turkey
| | - Jos Lelieveld
- The Cyprus Institute, Climate and Atmosphere Research Centre (CARE-C), 20 Konstantinou Kavafi Street, 2121, Aglantzia, Nicosia, Cyprus.,Max Planck Institute for Chemistry, 55128, Mainz, Germany
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Beeton NJ, Wilkins A, Ickowicz A, Hayes KR, Hosack GR. Spatial modelling for population replacement of mosquito vectors at continental scale. PLoS Comput Biol 2022; 18:e1009526. [PMID: 35648783 PMCID: PMC9191746 DOI: 10.1371/journal.pcbi.1009526] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 06/13/2022] [Accepted: 04/22/2022] [Indexed: 11/24/2022] Open
Abstract
Malaria is one of the deadliest vector-borne diseases in the world. Researchers are developing new genetic and conventional vector control strategies to attempt to limit its burden. Novel control strategies require detailed safety assessment to ensure responsible and successful deployments. Anopheles gambiae sensu stricto (s.s.) and Anopheles coluzzii, two closely related subspecies within the species complex Anopheles gambiae sensu lato (s.l.), are among the dominant malaria vectors in sub-Saharan Africa. These two subspecies readily hybridise and compete in the wild and are also known to have distinct niches, each with spatially and temporally varying carrying capacities driven by precipitation and land use factors. We model the spread and persistence of a population-modifying gene drive system in these subspecies across sub-Saharan Africa by simulating introductions of genetically modified mosquitoes across the African mainland and its offshore islands. We explore transmission of the gene drive between the two subspecies that arise from different hybridisation mechanisms, the effects of both local dispersal and potential wind-aided migration to the spread, and the development of resistance to the gene drive. Given the best current available knowledge on the subspecies’ life histories, we find that an introduced gene drive system with typical characteristics can plausibly spread from even distant offshore islands to the African mainland with the aid of wind-driven migration, with resistance beginning to take over within a decade. Our model accounts for regional to continental scale mechanisms, and demonstrates a range of realistic dynamics including the effect of prevailing wind on spread and spatio-temporally varying carrying capacities for subspecies. As a result, it is well-placed to answer future questions relating to mosquito gene drives as important life history parameters become better understood. Conventional control methods have dramatically reduced malaria, but it still kills over 300,000 children in Africa each year, and this number could increase as their effectiveness wanes. Novel control methods using gene drives rapidly reduce or modify malaria vector populations in laboratory settings, and hence are now being considered for field applications. We use modelling to assess how a gene drive might spread and persist in the malaria-carrying subspecies Anopheles gambiae sensu stricto (s.s.) and Anopheles coluzzii. These two subspecies interbreed and compete, so we model how these interactions affect the spread of the drive at a continental scale. In scenarios that allow mosquitoes to travel on prevailing wind currents, we find that a gene drive can potentially spread across national borders—and jump from offshore islands to the African mainland—but spread is eventually arrested when the drive allele is ousted by a resistant allele. As we learn more about the population dynamics of both genetically modified and wild mosquitoes, and as gene drive systems are further developed to allow local containment and evade resistance, our model will be able to answer more detailed questions about how they can be applied in the field effectively and safely.
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Affiliation(s)
- Nicholas J. Beeton
- Data61, CSIRO, 3 Castray Esplanade, Battery Point TAS, Australia
- * E-mail: (NJB); (AW)
| | - Andrew Wilkins
- Mineral Resources, CSIRO, 1 Technology Court, Pullenvale QLD, Australia
- * E-mail: (NJB); (AW)
| | - Adrien Ickowicz
- Data61, CSIRO, 3 Castray Esplanade, Battery Point TAS, Australia
| | - Keith R. Hayes
- Data61, CSIRO, 3 Castray Esplanade, Battery Point TAS, Australia
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McMahon A, Mihretie A, Ahmed AA, Lake M, Awoke W, Wimberly MC. Remote sensing of environmental risk factors for malaria in different geographic contexts. Int J Health Geogr 2021; 20:28. [PMID: 34120599 PMCID: PMC8201719 DOI: 10.1186/s12942-021-00282-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 06/03/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Despite global intervention efforts, malaria remains a major public health concern in many parts of the world. Understanding geographic variation in malaria patterns and their environmental determinants can support targeting of malaria control and development of elimination strategies. METHODS We used remotely sensed environmental data to analyze the influences of environmental risk factors on malaria cases caused by Plasmodium falciparum and Plasmodium vivax from 2014 to 2017 in two geographic settings in Ethiopia. Geospatial datasets were derived from multiple sources and characterized climate, vegetation, land use, topography, and surface water. All data were summarized annually at the sub-district (kebele) level for each of the two study areas. We analyzed the associations between environmental data and malaria cases with Boosted Regression Tree (BRT) models. RESULTS We found considerable spatial variation in malaria occurrence. Spectral indices related to land cover greenness (NDVI) and moisture (NDWI) showed negative associations with malaria, as the highest malaria rates were found in landscapes with low vegetation cover and moisture during the months that follow the rainy season. Climatic factors, including precipitation and land surface temperature, had positive associations with malaria. Settlement structure also played an important role, with different effects in the two study areas. Variables related to surface water, such as irrigated agriculture, wetlands, seasonally flooded waterbodies, and height above nearest drainage did not have strong influences on malaria. CONCLUSION We found different relationships between malaria and environmental conditions in two geographically distinctive areas. These results emphasize that studies of malaria-environmental relationships and predictive models of malaria occurrence should be context specific to account for such differences.
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Affiliation(s)
- Andrea McMahon
- Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK USA
| | - Abere Mihretie
- Health, Development, and Anti-Malaria Association, Addis Ababa, Ethiopia
| | - Adem Agmas Ahmed
- Malaria Control and Elimination Partnership in Africa, Bahir Dar, Ethiopia
| | | | - Worku Awoke
- School of Public Health, Bahir Dar University, Bahir Dar, Ethiopia
| | - Michael Charles Wimberly
- Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK USA
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Mbouna AD, Tompkins AM, Lenouo A, Asare EO, Yamba EI, Tchawoua C. Modelled and observed mean and seasonal relationships between climate, population density and malaria indicators in Cameroon. Malar J 2019; 18:359. [PMID: 31707994 PMCID: PMC6842545 DOI: 10.1186/s12936-019-2991-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Accepted: 10/31/2019] [Indexed: 11/17/2022] Open
Abstract
Background A major health burden in Cameroon is malaria, a disease that is sensitive to climate, environment and socio-economic conditions, but whose precise relationship with these drivers is still uncertain. An improved understanding of the relationship between the disease and its drivers, and the ability to represent these relationships in dynamic disease models, would allow such models to contribute to health mitigation and adaptation planning. This work collects surveys of malaria parasite ratio and entomological inoculation rate and examines their relationship with temperature, rainfall, population density in Cameroon and uses this analysis to evaluate a climate sensitive mathematical model of malaria transmission. Methods Co-located, climate and population data is compared to the results of 103 surveys of parasite ratio (PR) covering 18,011 people in Cameroon. A limited set of campaigns which collected year-long field-surveys of the entomological inoculation rate (EIR) are examined to determine the seasonality of disease transmission, three of the study locations are close to the Sanaga and Mefou rivers while others are not close to any permanent water feature. Climate-driven simulations of the VECTRI malaria model are evaluated with this analysis. Results The analysis of the model results shows the PR peaking at temperatures of approximately 22 °C to 26 °C, in line with recent work that has suggested a cooler peak temperature relative to the established literature, and at precipitation rates at 7 mm day−1, somewhat higher than earlier estimates. The malaria model is able to reproduce this broad behaviour, although the peak occurs at slightly higher temperatures than observed, while the PR peaks at a much lower rainfall rate of 2 mm day−1. Transmission tends to be high in rural and peri-urban relative to urban centres in both model and observations, although the model is oversensitive to population which could be due to the neglect of population movements, and differences in hydrological conditions, housing quality and access to healthcare. The EIR follows the seasonal rainfall with a lag of 1 to 2 months, and is well reproduced by the model, while in three locations near permanent rivers the annual cycle of malaria transmission is out of phase with rainfall and the model fails. Conclusion Malaria prevalence is maximum at temperatures of 24 to 26 °C in Cameroon and rainfall rates of approximately 4 to 6 mm day−1. The broad relationships are reproduced in a malaria model although prevalence is highest at a lower rainfall maximum of 2 mm day−1. In locations far from water bodies malaria transmission seasonality closely follows that of rainfall with a lag of 1 to 2 months, also reproduced by the model, but in locations close to a seasonal river the seasonality of malaria transmission is reversed due to pooling in the transmission to the dry season, which the model fails to capture.
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Affiliation(s)
- Amelie D Mbouna
- Laboratory for Environmental Modelling and Atmospheric Physics (LEMAP), Department of Physics, Faculty of Science, University of Yaoundé́ I, Yaoundé, Cameroon. .,Earth System Physics, Abdus Salam International Centre for Theoretical Physics (ICTP), Strada Costiera 11, Trieste, Italy.
| | - Adrian M Tompkins
- Earth System Physics, Abdus Salam International Centre for Theoretical Physics (ICTP), Strada Costiera 11, Trieste, Italy
| | - Andre Lenouo
- Department of Physics, Faculty of Science, University of Douala, Douala, Cameroon
| | - Ernest O Asare
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Yale University, New Haven, USA
| | - Edmund I Yamba
- Department of Physics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Clement Tchawoua
- Laboratory for Environmental Modelling and Atmospheric Physics (LEMAP), Department of Physics, Faculty of Science, University of Yaoundé́ I, Yaoundé, Cameroon
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11
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North AR, Burt A, Godfray HCJ. Modelling the potential of genetic control of malaria mosquitoes at national scale. BMC Biol 2019; 17:26. [PMID: 30922310 PMCID: PMC6440076 DOI: 10.1186/s12915-019-0645-5] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Accepted: 03/06/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The persistence of malaria in large parts of sub-Saharan Africa has motivated the development of novel tools to complement existing control programmes, including gene-drive technologies to modify mosquito vector populations. Here, we use a stochastic simulation model to explore the potential of using a driving-Y chromosome to suppress vector populations in a 106 km2 area of West Africa including all of Burkina Faso. RESULTS The consequence of driving-Y introductions is predicted to vary across the landscape, causing elimination of the target species in some regions and suppression in others. We explore how this variation is determined by environmental conditions, mosquito behaviour, and the properties of the gene-drive. Seasonality is particularly important, and we find population elimination is more likely in regions with mild dry seasons whereas suppression is more likely in regions with strong seasonality. CONCLUSIONS Despite the spatial heterogeneity, we suggest that repeated introductions of modified mosquitoes over a few years into a small fraction of human settlements may be sufficient to substantially reduce the overall number of mosquitoes across the entire geographic area.
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Affiliation(s)
- Ace R North
- Department of Zoology, University of Oxford, Oxford, UK.
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12
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Tompkins AM, Colón‐González FJ, Di Giuseppe F, Namanya DB. Dynamical Malaria Forecasts Are Skillful at Regional and Local Scales in Uganda up to 4 Months Ahead. GEOHEALTH 2019; 3:58-66. [PMID: 32159031 PMCID: PMC7038892 DOI: 10.1029/2018gh000157] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Revised: 11/02/2018] [Accepted: 01/04/2019] [Indexed: 06/10/2023]
Abstract
Malaria forecasts from dynamical systems have never been attempted at the health district or local clinic catchment scale, and so their usefulness for public health preparedness and response at the local level is fundamentally unknown. A pilot preoperational forecasting system is introduced in which the European Centre for Medium Range Weather Forecasts ensemble prediction system and seasonal climate forecasts of temperature and rainfall are used to drive the uncalibrated dynamical malaria model VECTRI to predict anomalies in transmission intensity 4 months ahead. It is demonstrated that the system has statistically significant skill at a number of sentinel sites in Uganda with high-quality data. Skill is also found at approximately 50% of the Ugandan health districts despite inherent uncertainties of unconfirmed health reports. A cost-loss economic analysis at three example sentinel sites indicates that the forecast system can have a positive economic benefit across a broad range of intermediate cost-loss ratios and frequency of transmission anomalies. We argue that such an analysis is a necessary first step in the attempt to translate climate-driven malaria information to policy-relevant decisions.
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Affiliation(s)
- Adrian M. Tompkins
- Earth System PhysicsAbdus Salam International Centre for Theoretical PhysicsTriesteItaly
| | - Felipe J. Colón‐González
- School of Environmental SciencesUniversity of East AngliaNorwichUK
- Tyndall Centre for Climate Change ResearchUniversity of East AngliaNorwichUK
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13
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Mukhtar AYA, Munyakazi JB, Ouifki R. Assessing the role of climate factors on malaria transmission dynamics in South Sudan. Math Biosci 2019; 310:13-23. [PMID: 30711479 DOI: 10.1016/j.mbs.2019.01.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Revised: 10/04/2018] [Accepted: 01/11/2019] [Indexed: 01/16/2023]
Abstract
Malaria is endemic in South Sudan and it is one of the most severe diseases in the war-torn nation. There has been much concern about whether the severity of its transmission might depend upon climatic conditions that are related to the reproduction of the single-cell parasite attaching to female mosquitoes, especially in high altitude areas. The country experiences two different climatic conditions; namely one tropical and the other hot and semi-arid. In this study, we aim to assess the potential impact of climatic conditions on malaria prevalence in these two climatically distinct regions of South Sudan. We develop and analyze a host-mosquito disease-based model that includes temperature and rainfall. The model has also been parameterized in a Bayesian framework using Bayesian Markov Chain Monte Carlo (MCMC). The mathematical analysis for this study has included equilibria, stability and a sensitivity index on the basic reproduction number R0. The threshold R0 is also used to provide a numerical basis for further refinement and prediction of the impact of climate variability on malaria transmission intensity over the study region. The study highlights the impact of various temperature values on the population dynamics of the mosquito.
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Affiliation(s)
- Abdulaziz Y A Mukhtar
- Department of Mathematics and Applied Mathematics, University of the Western Cape, Private Bag X17, Bellville 7535, South Africa; DST-NRF Centre of Excellence in Mathematical and Statistical Sciences (CoE-Mass), South Africa.
| | - Justin B Munyakazi
- Department of Mathematics and Applied Mathematics, University of the Western Cape, Private Bag X17, Bellville 7535, South Africa
| | - Rachid Ouifki
- Department of Mathematics and Applied Mathematics, Faculty of Natural & Agricultural Sciences, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa
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14
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Tompkins AM, Thomson MC. Uncertainty in malaria simulations in the highlands of Kenya: Relative contributions of model parameter setting, driving climate and initial condition errors. PLoS One 2018; 13:e0200638. [PMID: 30256799 PMCID: PMC6157844 DOI: 10.1371/journal.pone.0200638] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Accepted: 06/29/2018] [Indexed: 11/23/2022] Open
Abstract
In this study, experiments are conducted to gauge the relative importance of model, initial condition, and driving climate uncertainty for simulations of malaria transmission at a highland plantation in Kericho, Kenya. A genetic algorithm calibrates each of these three factors within their assessed prior uncertainty in turn to see which allows the best fit to a timeseries of confirmed cases. It is shown that for high altitude locations close to the threshold for transmission, the spatial representativeness uncertainty for climate, in particular temperature, dominates the uncertainty due to model parameter settings. Initial condition uncertainty plays little role after the first two years, and is thus important in the early warning system context, but negligible for decadal and climate change investigations. Thus, while reducing uncertainty in the model parameters would improve the quality of the simulations, the uncertainty in the temperature driving data is critical. It is emphasized that this result is a function of the mean climate of the location itself, and it is shown that model uncertainty would be relatively more important at warmer, lower altitude locations.
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Affiliation(s)
- Adrian M. Tompkins
- Earth System Physics, The Abdus Salam International Centre for Theoretical Physics (ICTP), Strada Costiera 11, Trieste, Italy
- * E-mail:
| | - Madeleine C. Thomson
- International Research Institute for Climate and Society, Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York, United States of America
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15
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Abiodun GJ, Witbooi PJ, Okosun KO, Maharaj R. Exploring the Impact of Climate Variability on Malaria Transmission Using a Dynamic Mosquito-Human Malaria Model. ACTA ACUST UNITED AC 2018; 10:88-100. [PMID: 30906484 PMCID: PMC6430130 DOI: 10.2174/1874279301810010088] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Introduction: The reasons for malaria resurgence mostly in Africa are yet to be well understood. Although the causes are often linked to regional climate change, it is important to understand the impact of climate variability on the dynamics of the disease. However, this is almost impossible without adequate long-term malaria data over the study areas. Methods: In this study, we develop a climate-based mosquito-human malaria model to study malaria dynamics in the human population over KwaZulu-Natal, one of the epidemic provinces in South Africa, from 1970-2005. We compare the model output with available observed monthly malaria cases over the province from September 1999 to December 2003. We further use the model outputs to explore the relationship between the climate variables (rainfall and temperature) and malaria incidence over the province using principal component analysis, wavelet power spectrum and wavelet coherence analysis. The model produces a reasonable fit with the observed data and in particular, it captures all the spikes in malaria prevalence. Results: Our results highlight the importance of climate factors on malaria transmission and show the seasonality of malaria epidemics over the province. Results from the principal component analyses further suggest that, there are two principal factors associated with climates variables and the model outputs. One of the factors indicate high loadings on Susceptible, Exposed and Infected human, while the other is more correlated with Susceptible and Recovered humans. However, both factors reveal the inverse correlation between Susceptible-Infected and Susceptible-Recovered humans respectively. Through the spectrum analysis, we notice a strong annual cycle of malaria incidence over the province and ascertain a dominant of one year periodicity. Consequently, our findings indicate that an average of 0 to 120-day lag is generally noted over the study period, but the 120-day lag is more associated with temperature than rainfall. This is consistence with other results obtained from our analyses that malaria transmission is more tightly coupled with temperature than with rainfall in KwaZulu-Natal province.
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Affiliation(s)
- Gbenga J Abiodun
- Research Unit, Foundation for Professional Development, Pretoria 0184, Republic of South Africa.,Department of Mathematics and Applied Mathematics, University of the Western Cape, Private Bag X17, Bellville7535, Republic of South Africa
| | - Peter J Witbooi
- Department of Mathematics and Applied Mathematics, University of the Western Cape, Private Bag X17, Bellville7535, Republic of South Africa
| | - Kazeem O Okosun
- Department of Mathematics, Vaal University of Technology, X021, Vanderbijlpark, 1900, Republic of South Africa
| | - Rajendra Maharaj
- Office of Malaria Research, South African Medical Research Council, Durban, Republic of South Africa
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16
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Eikenberry SE, Gumel AB. Mathematical modeling of climate change and malaria transmission dynamics: a historical review. J Math Biol 2018; 77:857-933. [PMID: 29691632 DOI: 10.1007/s00285-018-1229-7] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2017] [Revised: 03/16/2018] [Indexed: 12/24/2022]
Abstract
Malaria, one of the greatest historical killers of mankind, continues to claim around half a million lives annually, with almost all deaths occurring in children under the age of five living in tropical Africa. The range of this disease is limited by climate to the warmer regions of the globe, and so anthropogenic global warming (and climate change more broadly) now threatens to alter the geographic area for potential malaria transmission, as both the Plasmodium malaria parasite and Anopheles mosquito vector have highly temperature-dependent lifecycles, while the aquatic immature Anopheles habitats are also strongly dependent upon rainfall and local hydrodynamics. A wide variety of process-based (or mechanistic) mathematical models have thus been proposed for the complex, highly nonlinear weather-driven Anopheles lifecycle and malaria transmission dynamics, but have reached somewhat disparate conclusions as to optimum temperatures for transmission, and the possible effect of increasing temperatures upon (potential) malaria distribution, with some projecting a large increase in the area at risk for malaria, but others predicting primarily a shift in the disease's geographic range. More generally, both global and local environmental changes drove the initial emergence of P. falciparum as a major human pathogen in tropical Africa some 10,000 years ago, and the disease has a long and deep history through the present. It is the goal of this paper to review major aspects of malaria biology, methods for formalizing these into mathematical forms, uncertainties and controversies in proper modeling methodology, and to provide a timeline of some major modeling efforts from the classical works of Sir Ronald Ross and George Macdonald through recent climate-focused modeling studies. Finally, we attempt to place such mathematical work within a broader historical context for the "million-murdering Death" of malaria.
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Affiliation(s)
- Steffen E Eikenberry
- Global Security Initiative, Arizona State University, Tempe, AZ, USA. .,School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, USA.
| | - Abba B Gumel
- School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, USA
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17
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North AR, Godfray HCJ. Modelling the persistence of mosquito vectors of malaria in Burkina Faso. Malar J 2018; 17:140. [PMID: 29609598 PMCID: PMC5879775 DOI: 10.1186/s12936-018-2288-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2017] [Accepted: 03/21/2018] [Indexed: 11/26/2022] Open
Abstract
Background Populations of the Anopheles gambiae complex are found during the rainy season throughout West Africa, even in arid areas with long dry seasons during which mosquitoes appear to be absent. Several hypotheses have been proposed to explain this apparent paradox, including aestivation, dispersal between neighbouring settlements, and long distance migration using high-altitude wind currents. Methods An individual-based, spatially explicit model of mosquito populations was developed for a region of West Africa centred on, and including all of, Burkina Faso. Populations associated with human settlements were linked by dispersal and the model incorporated geospatial data on the distribution of settlements, water bodies and rainfall. Results Local dispersal (at rates consistent with experimental data) was necessary to explain observed patterns of rainy season populations across all of the simulation area, but by itself failed to account for the presence of populations in the arid North (the Sahel). The presence of rare dry-season larval sites could explain these northern populations, but seems inconsistent with field surveys. Aestivation by female mosquitoes explained rainy-season populations in all but the very sparsest and driest areas of human habitation, while long-distance migration based on annual wind patterns could account for all observed populations. Conclusions Modelling studies such as this can help assess the potential validity of different hypotheses and suggest priority areas for experimental study. In particular, the results highlight a shortage of empirical research on mosquito dispersal between neighbouring settlements, which may be critically important to the continued presence of many mosquito populations in West Africa. Further research that establishes the extent to which mosquitoes aestivate, and migrate using high altitude winds, is also much needed to understand Sahelian mosquito populations. Electronic supplementary material The online version of this article (10.1186/s12936-018-2288-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Ace R North
- Department of Zoology, University of Oxford, Woodstock Road, Oxford, OX2 6GG, UK.
| | - H Charles J Godfray
- Department of Zoology, University of Oxford, Woodstock Road, Oxford, OX2 6GG, UK
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18
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Alam MZ, Niaz Arifin SM, Al-Amin HM, Alam MS, Rahman MS. A spatial agent-based model of Anopheles vagus for malaria epidemiology: examining the impact of vector control interventions. Malar J 2017; 16:432. [PMID: 29078771 PMCID: PMC5658966 DOI: 10.1186/s12936-017-2075-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Accepted: 10/19/2017] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND Malaria, being a mosquito-borne infectious disease, is still one of the most devastating global health issues. The malaria vector Anopheles vagus is widely distributed in Asia and a dominant vector in Bandarban, Bangladesh. However, despite its wide distribution, no agent based model (ABM) of An. vagus has yet been developed. Additionally, its response to combined vector control interventions has not been examined. METHODS A spatial ABM, denoted as ABM[Formula: see text], was designed and implemented based on the biological attributes of An. vagus by modifying an established, existing ABM of Anopheles gambiae. Environmental factors such as temperature and rainfall were incorporated into ABM[Formula: see text] using daily weather profiles. Real-life field data of Bandarban were used to generate landscapes which were used in the simulations. ABM[Formula: see text] was verified and validated using several standard techniques and against real-life field data. Using artificial landscapes, the individual and combined efficacies of existing vector control interventions are modeled, applied, and examined. RESULTS Simulated female abundance curves generated by ABM[Formula: see text] closely follow the patterns observed in the field. Due to the use of daily temperature and rainfall data, ABM[Formula: see text] was able to generate seasonal patterns for a particular area. When two interventions were applied with parameters set to mid-ranges, ITNs/LLINs with IRS produced better results compared to the other cases. Moreover, any intervention combined with ITNs/LLINs yielded better results. Not surprisingly, three interventions applied in combination generate best results compared to any two interventions applied in combination. CONCLUSIONS Output of ABM[Formula: see text] showed high sensitivity to real-life field data of the environmental factors and the landscape of a particular area. Hence, it is recommended to use the model for a given area in connection to its local field data. For applying combined interventions, three interventions altogether are highly recommended whenever possible. It is also suggested that ITNs/LLINs with IRS can be applied when three interventions are not available.
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Affiliation(s)
- Md. Zahangir Alam
- Department of Computer Science & Engineering (CSE), Bangladesh University of Engineering & Technology (BUET), ECE Building, West Palasi, Dhaka, 1205 Bangladesh
| | - S. M. Niaz Arifin
- Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, Indiana 46556 USA
| | - Hasan Mohammad Al-Amin
- International Centre for Diarrhoeal Disease Research Bangladesh (icddr,b), Dhaka, 1212 Bangladesh
| | - Mohammad Shafiul Alam
- International Centre for Diarrhoeal Disease Research Bangladesh (icddr,b), Dhaka, 1212 Bangladesh
| | - M. Sohel Rahman
- Department of Computer Science & Engineering (CSE), Bangladesh University of Engineering & Technology (BUET), ECE Building, West Palasi, Dhaka, 1205 Bangladesh
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Farajzadeh M, Halimi M, Ghavidel Y, Delavari M. Spatiotemporal Anopheles Population Dynamics, Response to Climatic Conditions: The Case of Chabahar, South Baluchistan, Iran. Ann Glob Health 2017; 81:694-704. [PMID: 27036728 DOI: 10.1016/j.aogh.2015.12.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND An understanding of the factors that affect the abundance of Anopheline species provides an opportunity to better understand the dynamics of malaria transmission in different regions. Chabahar, located south east of Iran, is the most malarious region in the country. OBJECTIVE The main aim of this study was to quantify the spatiotemporal Anopheles population dynamics, response to climatic conditions in Chabahar. METHODS Satellite-based and land-based climatic data were used as explanatory variables. Monthly caught mosquitoes in 6 village sites of Chabahar were used as dependent variable. The spatiotemporal associations were first investigated by inspection of scatter plots and single variable regression analysis. A multivariate linear regression model was developed to reveal the association between environmental variables and the monthly mosquito abundance at a 95% confidence level (P ≤ 0.5). FINDINGS Results indicated that Anopheles mosquitoes can be found all year in Chabahar with 2 significant seasonal peaks from March to June (primary peak) and September to November (secondary peak). Results of the present study showed that 0.77 of yearly mosquito abundance emerges in the thermal range of 24°C to 30°C and the humidity range of 0.70 to 0.80 in Chabahar. CONCLUSION According to the developed multivariate linear model, 0.88 of temporal variance of mosquito abundance, nighttime land surface temperature, and relative humidity of 15 Universal Time Coordinated (18.30 Iran) are the main drivers of mosquito population dynamics in Chabahar.
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Affiliation(s)
| | - Mansour Halimi
- Department of Climatology, TarbiatModares University, Tehran, Iran.
| | - Yousef Ghavidel
- Department of Climatology, TarbiatModares University, Tehran, Iran
| | - Mahdi Delavari
- Department of Medical Parasitology and Mycology, Faculty of Medicine, Kashan University of Medical Science, Kashan, Iran
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20
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Abiodun GJ, Maharaj R, Witbooi P, Okosun KO. Modelling the influence of temperature and rainfall on the population dynamics of Anopheles arabiensis. Malar J 2016; 15:364. [PMID: 27421769 PMCID: PMC4946230 DOI: 10.1186/s12936-016-1411-6] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2016] [Accepted: 06/22/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Malaria continues to be one of the most devastating diseases in the world, killing more humans than any other infectious disease. Malaria parasites are entirely dependent on Anopheles mosquitoes for transmission. For this reason, vector population dynamics is a crucial determinant of malaria risk. Consequently, it is important to understand the biology of malaria vector mosquitoes in the study of malaria transmission. Temperature and precipitation also play a significant role in both aquatic and adult stages of the Anopheles. METHODS In this study, a climate-based, ordinary-differential-equation model is developed to analyse how temperature and the availability of water affect mosquito population size. In the model, the influence of ambient temperature on the development and the mortality rate of Anopheles arabiensis is considered over a region in KwaZulu-Natal Province, South Africa. In particular, the model is used to examine the impact of climatic factors on the gonotrophic cycle and the dynamics of mosquito population over the study region. RESULTS The results fairly accurately quantify the seasonality of the population of An. arabiensis over the region and also demonstrate the influence of climatic factors on the vector population dynamics. The model simulates the population dynamics of both immature and adult An. arabiensis. The simulated larval density produces a curve which is similar to observed data obtained from another study. CONCLUSION The model is efficiently developed to predict An. arabiensis population dynamics, and to assess the efficiency of various control strategies. In addition, the model framework is built to accommodate human population dynamics with the ability to predict malaria incidence in future.
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Affiliation(s)
- Gbenga J Abiodun
- Department of Mathematics and Applied Mathematics, University of the Western Cape, Private Bag X17, Bellville, 7535, Republic of South Africa
| | - Rajendra Maharaj
- Office of Malaria Research, South African Medical Research Council, Durban, Republic of South Africa.
| | - Peter Witbooi
- Department of Mathematics and Applied Mathematics, University of the Western Cape, Private Bag X17, Bellville, 7535, Republic of South Africa
| | - Kazeem O Okosun
- Department of Mathematics, Vaal University of Technology, Private Bag X021, Andries Potgieter Blvrd, Vanderbijlpark, 1900, Republic of South Africa
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Jia P, Lu L, Chen X, Chen J, Guo L, Yu X, Liu Q. A climate-driven mechanistic population model of Aedes albopictus with diapause. Parasit Vectors 2016; 9:175. [PMID: 27009065 PMCID: PMC4806478 DOI: 10.1186/s13071-016-1448-y] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2015] [Accepted: 03/12/2016] [Indexed: 01/19/2023] Open
Abstract
Background The mosquito Aedes albopitus is a competent vector for the transmission of many blood-borne pathogens. An important factor that affects the mosquitoes’ development and spreading is climate, such as temperature, precipitation and photoperiod. Existing climate-driven mechanistic models overlook the seasonal pattern of diapause, referred to as the survival strategy of mosquito eggs being dormant and unable to hatch under extreme weather. With respect to diapause, several issues remain unaddressed, including identifying the time when diapause eggs are laid and hatched under different climatic conditions, demarcating the thresholds of diapause and non-diapause periods, and considering the mortality rate of diapause eggs. Methods Here we propose a generic climate-driven mechanistic population model of Ae. albopitus applicable to most Ae. albopictus-colonized areas. The new model is an improvement over the previous work by incorporating the diapause behaviors with many modifications to the stage-specific mechanism of the mosquitoes’ life-cycle. monthly Container Index (CI) of Ae. albopitus collected in two Chinese cities, Guangzhou and Shanghai is used for model validation. Results The simulation results by the proposed model is validated with entomological field data by the Pearson correlation coefficient r2 in Guangzhou (r2 = 0.84) and in Shanghai (r2 = 0.90). In addition, by consolidating the effect of diapause-related adjustments and temperature-related parameters in the model, the improvement is significant over the basic model. Conclusions The model highlights the importance of considering diapause in simulating Ae. albopitus population. It also corroborates that temperature and photoperiod are significant in affecting the population dynamics of the mosquito. By refining the relationship between Ae. albopitus population and climatic factors, the model serves to establish a mechanistic relation to the growth and decline of the species. Understanding this relationship in a better way will benefit studying the transmission and the spatiotemporal distribution of mosquito-borne epidemics and eventually facilitating the early warning and control of the diseases.
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Affiliation(s)
- Pengfei Jia
- College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
| | - Liang Lu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, China CDC, Beijing, 102206, China
| | - Xiang Chen
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China. .,Department of Emergency Management, Arkansas Tech University, Russellville, Arkansas, 72801, USA.
| | - Jin Chen
- College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China.,State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China
| | - Li Guo
- College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China
| | - Xiao Yu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, China CDC, Beijing, 102206, China
| | - Qiyong Liu
- State Key Laboratory of Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, National Institute for Communicable Disease Control and Prevention, China CDC, Beijing, 102206, China
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A Regional Model for Malaria Vector Developmental Habitats Evaluated Using Explicit, Pond-Resolving Surface Hydrology Simulations. PLoS One 2016; 11:e0150626. [PMID: 27003834 PMCID: PMC4803214 DOI: 10.1371/journal.pone.0150626] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Accepted: 02/17/2016] [Indexed: 11/26/2022] Open
Abstract
Dynamical malaria models can relate precipitation to the availability of vector breeding sites using simple models of surface hydrology. Here, a revised scheme is developed for the VECTRI malaria model, which is evaluated alongside the default scheme using a two year simulation by HYDREMATS, a 10 metre resolution, village-scale model that explicitly simulates individual ponds. Despite the simplicity of the two VECTRI surface hydrology parametrization schemes, they can reproduce the sub-seasonal evolution of fractional water coverage. Calibration of the model parameters is required to simulate the mean pond fraction correctly. The default VECTRI model tended to overestimate water fraction in periods subject to light rainfall events and underestimate it during periods of intense rainfall. This systematic error was improved in the revised scheme by including the a parametrization for surface run-off, such that light rainfall below the initial abstraction threshold does not contribute to ponds. After calibration of the pond model, the VECTRI model was able to simulate vector densities that compared well to the detailed agent based model contained in HYDREMATS without further parameter adjustment. Substituting local rain-gauge data with satellite-retrieved precipitation gave a reasonable approximation, raising the prospects for regional malaria simulations even in data sparse regions. However, further improvements could be made if a method can be derived to calibrate the key hydrology parameters of the pond model in each grid cell location, possibly also incorporating slope and soil texture.
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Erguler K, Smith-Unna SE, Waldock J, Proestos Y, Christophides GK, Lelieveld J, Parham PE. Large-Scale Modelling of the Environmentally-Driven Population Dynamics of Temperate Aedes albopictus (Skuse). PLoS One 2016; 11:e0149282. [PMID: 26871447 PMCID: PMC4752251 DOI: 10.1371/journal.pone.0149282] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2015] [Accepted: 01/03/2016] [Indexed: 01/04/2023] Open
Abstract
The Asian tiger mosquito, Aedes albopictus, is a highly invasive vector species. It is a proven vector of dengue and chikungunya viruses, with the potential to host a further 24 arboviruses. It has recently expanded its geographical range, threatening many countries in the Middle East, Mediterranean, Europe and North America. Here, we investigate the theoretical limitations of its range expansion by developing an environmentally-driven mathematical model of its population dynamics. We focus on the temperate strain of Ae. albopictus and compile a comprehensive literature-based database of physiological parameters. As a novel approach, we link its population dynamics to globally-available environmental datasets by performing inference on all parameters. We adopt a Bayesian approach using experimental data as prior knowledge and the surveillance dataset of Emilia-Romagna, Italy, as evidence. The model accounts for temperature, precipitation, human population density and photoperiod as the main environmental drivers, and, in addition, incorporates the mechanism of diapause and a simple breeding site model. The model demonstrates high predictive skill over the reference region and beyond, confirming most of the current reports of vector presence in Europe. One of the main hypotheses derived from the model is the survival of Ae. albopictus populations through harsh winter conditions. The model, constrained by the environmental datasets, requires that either diapausing eggs or adult vectors have increased cold resistance. The model also suggests that temperature and photoperiod control diapause initiation and termination differentially. We demonstrate that it is possible to account for unobserved properties and constraints, such as differences between laboratory and field conditions, to derive reliable inferences on the environmental dependence of Ae. albopictus populations.
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Affiliation(s)
- Kamil Erguler
- Energy, Environment and Water Research Center, The Cyprus Institute, 2121 Aglantzia, Nicosia, Cyprus
- * E-mail: (KE); (PEP)
| | - Stephanie E. Smith-Unna
- Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge, CB2 3EA, United Kingdom
- Sainsbury Laboratory, University of Cambridge, Bateman Street, Cambridge, CB2 1LR, United Kingdom
| | - Joanna Waldock
- Energy, Environment and Water Research Center, The Cyprus Institute, 2121 Aglantzia, Nicosia, Cyprus
- Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Yiannis Proestos
- Computation-based Science and Technology Research Center, The Cyprus Institute, 2121 Aglantzia, Nicosia, Cyprus
| | - George K. Christophides
- Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
- Computation-based Science and Technology Research Center, The Cyprus Institute, 2121 Aglantzia, Nicosia, Cyprus
| | - Jos Lelieveld
- Energy, Environment and Water Research Center, The Cyprus Institute, 2121 Aglantzia, Nicosia, Cyprus
- Department of Atmospheric Chemistry, Max Planck Institute for Chemistry, D-55128 Mainz, Germany
| | - Paul E. Parham
- Department of Public Health and Policy, Faculty of Health and Life Sciences, University of Liverpool, Liverpool L69 3GL, United Kingdom
- Grantham Institute for Climate Change, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, St. Mary’s campus, Imperial College London, London W2 1PG, United Kingdom
- * E-mail: (KE); (PEP)
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AGUSTO FB, GUMEL AB, PARHAM PE. QUALITATIVE ASSESSMENT OF THE ROLE OF TEMPERATURE VARIATIONS ON MALARIA TRANSMISSION DYNAMICS. J BIOL SYST 2015. [DOI: 10.1142/s0218339015500308] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
A new mechanistic deterministic model for assessing the impact of temperature variability on malaria transmission dynamics is developed. Sensitivity and uncertainty analyses of the model parameters reveal that, for temperature values in the range 16–[Formula: see text]C, the three parameters with the greatest influence on disease dynamics are the mosquito carrying capacity, transmission probability per contact for susceptible mosquitoes and human recruitment rate. This study emphasizes the combined use of mosquito-reduction strategies and personal protection against mosquito bites during periods when the mean monthly temperatures are in the range 16.7–25[Formula: see text]C. For higher monthly mean temperatures in the range 26–34[Formula: see text]C, mosquito-reduction strategies should be emphasized ahead of personal protection. Numerical simulations of the model reveal that mosquito maturation rate has a minimum sensitivity (to the associated reproduction threshold of the model) at 24[Formula: see text]C and maximum at 30[Formula: see text]C. The mosquito biting rate has maximum sensitivity at 26[Formula: see text]C, while the minimum value for the transmission probability per bite for susceptible mosquitoes occurs at 24[Formula: see text]C. Furthermore, it is shown, using mean monthly temperature data from 67 cities across the four regions of sub-Saharan Africa, that malaria burden (measured in terms of the total number of new cases of infection) increases with increasing temperature in the range 16–28[Formula: see text]C and decreases for temperature values above 28[Formula: see text]C in West Africa, 27[Formula: see text]C in Central Africa, 26[Formula: see text]C in East Africa and 25[Formula: see text]C in South Africa. These findings, which support and complement a recent study by other authors, reinforce the potential importance of temperature and temperature variability on future malaria transmission trends. Further simulations show that mechanistic malaria transmission models that do not incorporate temperature variability may under-estimate disease burden for temperature values in the range 23–27[Formula: see text]C, and over-estimate disease burden for temperature values in the ranges 16–22[Formula: see text]C and 28–32[Formula: see text]C. Additionally, models that do not explicitly incorporate the dynamics of immature mosquitoes may under- or over-estimate malaria burden, depending on mosquito abundance and mean monthly temperature profile in the community.
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Affiliation(s)
- F. B. AGUSTO
- Department of Ecology and Evolutionary Biology University of Kansas, Lawrence, KS 66045, USA
| | - A. B. GUMEL
- School of Mathematical and Statistical Sciences Arizona State University Tempe, Arizona 85287-1804, USA
| | - P. E. PARHAM
- Department of Public Health and Policy Faculty of Health and Life Sciences University of Liverpool Liverpool L69 3GL, UK
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Parham PE, Hughes DA. Climate influences on the cost-effectiveness of vector-based interventions against malaria in elimination scenarios. Philos Trans R Soc Lond B Biol Sci 2015; 370:rstb.2013.0557. [PMID: 25688017 DOI: 10.1098/rstb.2013.0557] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Despite the dependence of mosquito population dynamics on environmental conditions, the associated impact of climate and climate change on present and future malaria remains an area of ongoing debate and uncertainty. Here, we develop a novel integration of mosquito, transmission and economic modelling to assess whether the cost-effectiveness of indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs) against Plasmodium falciparum transmission by Anopheles gambiae s.s. mosquitoes depends on climatic conditions in low endemicity scenarios. We find that although temperature and rainfall affect the cost-effectiveness of IRS and/or LLIN scale-up, whether this is sufficient to influence policy depends on local endemicity, existing interventions, host immune response to infection and the emergence rate of insecticide resistance. For the scenarios considered, IRS is found to be more cost-effective than LLINs for the same level of scale-up, and both are more cost-effective at lower mean precipitation and higher variability in precipitation and temperature. We also find that the dependence of peak transmission on mean temperature translates into optimal temperatures for vector-based intervention cost-effectiveness. Further cost-effectiveness analysis that accounts for country-specific epidemiological and environmental heterogeneities is required to assess optimal intervention scale-up for elimination and better understand future transmission trends under climate change.
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Affiliation(s)
- Paul E Parham
- Department of Public Health and Policy, University of Liverpool, London, EC2A 1AG, UK
| | - Dyfrig A Hughes
- Centre for Health Economics and Medicines Evaluation, Bangor University, Bangor, LL57 2PZ, UK
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26
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Bangs MJ, Taai K, Howard TM, Cook S, Harbach RE. The mosquito Anopheles (Cellia) oreios sp. n., formerly species 6 of the Australasian Anopheles farauti complex, and a critical review of its biology and relation to disease. MEDICAL AND VETERINARY ENTOMOLOGY 2015; 29:68-81. [PMID: 25532420 DOI: 10.1111/mve.12092] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2014] [Revised: 09/12/2014] [Accepted: 09/23/2014] [Indexed: 06/04/2023]
Abstract
Species 6 of the Australasian Anopheles farauti sibling species complex (Diptera: Culicidae) is described and formally named Anopheles oreios Bangs & Harbach, sp. n. Adult, pupal and fourth-instar larval specimens collected in the Baliem Valley, Papua Province, Indonesia, are characterized and compared with those of Anopheles farauti, Anopheles hinesorum, Anopheles irenicus and Anopheles torresiensis (formerly informally denoted as species 1, 2, 7 and 3, respectively). The variable wings of adult females, the male genitalia, the pupa and the fourth-instar larva of An. oreios are illustrated and DNA sequence data are included for regions coding for sections of the mitochondrial COI and COII genes. The biology of An. oreios and its relation to malaria transmission are discussed in detail and contrasted with the biology and disease relations of some members of the An. farauti and Anopheles punctulatus sibling species complexes.
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Affiliation(s)
- M J Bangs
- Public Health and Malaria Control Department, International SOS, Kuala Kencana, Indonesia
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27
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Komen K, Olwoch J, Rautenbach H, Botai J, Adebayo A. Long-run relative importance of temperature as the main driver to malaria transmission in Limpopo Province, South Africa: a simple econometric approach. ECOHEALTH 2015; 12:131-43. [PMID: 25515074 DOI: 10.1007/s10393-014-0992-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2012] [Revised: 10/10/2014] [Accepted: 10/13/2014] [Indexed: 05/15/2023]
Abstract
Malaria in Limpopo Province of South Africa is shifting and now observed in originally non-malaria districts, and it is unclear whether climate change drives this shift. This study examines the distribution of malaria at district level in the province, determines direction and strength of the linear relationship and causality between malaria with the meteorological variables (rainfall and temperature) and ascertains their short- and long-run variations. Spatio-temporal method, Correlation analysis and econometric methods are applied. Time series monthly meteorological data (1998-2007) were obtained from South Africa Weather Services, while clinical malaria data came from Malaria Control Centre in Tzaneen (Limpopo Province) and South African Department of Health. We find that malaria changes and pressures vary in different districts with a strong positive correlation between temperature with malaria, r = 0.5212, and a weak positive relationship for rainfall, r = 0.2810. Strong unidirectional causality runs from rainfall and temperature to malaria cases (and not vice versa): F (1, 117) = 3.89, ρ = 0.0232 and F (1, 117) = 20.08, P < 0.001 and between rainfall and temperature, a bi-directional causality exists: F (1, 117) = 19.80; F (1,117) = 17.14, P < 0.001, respectively, meaning that rainfall affects temperature and vice versa. Results show evidence of strong existence of a long-run relationship between climate variables and malaria, with temperature maintaining very high level of significance than rainfall. Temperature, therefore, is more important in influencing malaria transmission in Limpopo Province.
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Affiliation(s)
- Kibii Komen
- Geoinformatics and Meteorology - Center for Environmental Studies, Department of Geography, University of Pretoria, Pretoria, 0002, South Africa,
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Wallace DI, Southworth BS, Shi X, Chipman JW, Githeko AK. A comparison of five malaria transmission models: benchmark tests and implications for disease control. Malar J 2014; 13:268. [PMID: 25011942 PMCID: PMC4105118 DOI: 10.1186/1475-2875-13-268] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2014] [Accepted: 06/27/2014] [Indexed: 11/17/2022] Open
Abstract
Background Models for malaria transmission are usually compared based on the quantities tracked, the form taken by each term in the equations, and the qualitative properties of the systems at equilibrium. Here five models are compared in detail in order to develop a set of performance measures that further illuminate the differences among models. Methods Five models of malaria transmission are compared. Parameters are adjusted to correspond to similar biological quantities across models. Nine choices of parameter sets/initial conditions are tested for all five models. The relationship between malaria incidence in humans and (1) malaria incidence in vectors, (2) man-biting rate, and (3) entomological inoculation rate (EIR) at equilibrium is tested for all models. A sensitivity analysis for all models is conducted at all parameter sets. Overall sensitivities are ranked for each of the five models. A set of simple control interventions is tested on two of the models. Results Four of these models behave consistently over a set of nine choices of parameters and initial conditions, with one behaving significantly differently. Two of the models do not match reported entomological inoculation rate data well. The sensitivity profiles, although consistently having similar top parameters, vary not only between models but among choices of parameters and initial conditions. A numerical experiment on two of the models illustrates the effect of these differences on control strategies, showing significant differences between models in predicting which of the control measures are more effective. Conclusions A set of benchmark tests based on performance measures are developed to be used on any proposed malaria transmission model to test its overall behaviour in comparison to both other models and data sets.
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29
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Gimonneau G, Brossette L, Mamaï W, Dabiré RK, Simard F. Larval competition between An. coluzzii and An. gambiae in insectary and semi-field conditions in Burkina Faso. Acta Trop 2014; 130:155-61. [PMID: 24269743 DOI: 10.1016/j.actatropica.2013.11.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2013] [Revised: 11/01/2013] [Accepted: 11/09/2013] [Indexed: 12/20/2022]
Abstract
Competition in mosquito larvae is common and different ecological context could change competitive advantage between species. Here, larval competition between the widely sympatric African malaria mosquitoes, Anopheles coluzzii and Anopheles gambiae were investigated in controlled insectary conditions using individuals from laboratory colonies and under ambient conditions using wild mosquitoes in a semi-field enclosure in western Burkina Faso. Larvae of both species were reared in trays at the same larval density and under the same feeding regimen in either single-species or mixed-species populations at varying species ratios reflecting 0%, 25%, 50% and 75% of competitor species. In the insectaries, where environmental variations are controlled, larvae of the An. coluzzii colony developed faster and with lower mortality than larvae of the An. gambiae colony (8.8±0.1 days and 21±3% mortality vs. 9.5±0.1 days and 32±3% mortality, respectively). Although there was no significant effect of competition on these phenotypic traits in any species, there was a significant trend for higher fitness of the An. coluzzii colony when competing with An. gambiae under laboratory conditions (i.e. lower development time and increased wing length at emergence, Cuzik's tests, P<0.05). In semi-field experiments, competition affected the life history traits of both species in a different way. Larvae of An. gambiae tended to reduce development time when in competition with An. coluzzii (Cuzick's test, P=0.002) with no impact either on mortality or size at emergence. On the other hand, An. coluzzii showed a significant trend for reduced larval mortality with increasing competition pressure (Cuzick's test, P=0.037) and production of smaller females when grown together with An. gambiae (Cuzick's test, P=0.002). Our results hence revealed that competitive interactions between larvae of the two species are context dependent. They further call for caution when exploring ecological processes using inbred laboratory colonies in this system of utmost medical importance.
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Affiliation(s)
- Geoffrey Gimonneau
- Institut de Recherche pour le Développement (IRD), UMR 224-CNRS 5290-Université de Montpellier 1-Université de Montpellier 2 MIVEGEC (Maladies Infectieuses et Vecteurs: Ecologie, Genetique, Evolution et Contrôle), team BEES (Biology, Ecology and Evolution of vector Systems), 911 Avenue Agropolis, BP 64501, 34394 Montpellier, France; Institut de Recherche en Sciences de la Santé (IRSS), Direction Régionale de l'Ouest (DRO), 399 Avenue de la Liberté, 01 BP 545 Bobo Dioulasso, Burkina Faso.
| | - Lou Brossette
- Institut de Recherche pour le Développement (IRD), UMR 224-CNRS 5290-Université de Montpellier 1-Université de Montpellier 2 MIVEGEC (Maladies Infectieuses et Vecteurs: Ecologie, Genetique, Evolution et Contrôle), team BEES (Biology, Ecology and Evolution of vector Systems), 911 Avenue Agropolis, BP 64501, 34394 Montpellier, France.
| | - Wadaka Mamaï
- Institut de Recherche pour le Développement (IRD), UMR 224-CNRS 5290-Université de Montpellier 1-Université de Montpellier 2 MIVEGEC (Maladies Infectieuses et Vecteurs: Ecologie, Genetique, Evolution et Contrôle), team BEES (Biology, Ecology and Evolution of vector Systems), 911 Avenue Agropolis, BP 64501, 34394 Montpellier, France; Institut de Recherche en Sciences de la Santé (IRSS), Direction Régionale de l'Ouest (DRO), 399 Avenue de la Liberté, 01 BP 545 Bobo Dioulasso, Burkina Faso.
| | - Roch K Dabiré
- Institut de Recherche en Sciences de la Santé (IRSS), Direction Régionale de l'Ouest (DRO), 399 Avenue de la Liberté, 01 BP 545 Bobo Dioulasso, Burkina Faso.
| | - Frédéric Simard
- Institut de Recherche pour le Développement (IRD), UMR 224-CNRS 5290-Université de Montpellier 1-Université de Montpellier 2 MIVEGEC (Maladies Infectieuses et Vecteurs: Ecologie, Genetique, Evolution et Contrôle), team BEES (Biology, Ecology and Evolution of vector Systems), 911 Avenue Agropolis, BP 64501, 34394 Montpellier, France; Institut de Recherche en Sciences de la Santé (IRSS), Direction Régionale de l'Ouest (DRO), 399 Avenue de la Liberté, 01 BP 545 Bobo Dioulasso, Burkina Faso.
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Yamana TK, Eltahir EAB. Incorporating the effects of humidity in a mechanistic model of Anopheles gambiae mosquito population dynamics in the Sahel region of Africa. Parasit Vectors 2013; 6:235. [PMID: 23938022 PMCID: PMC3750695 DOI: 10.1186/1756-3305-6-235] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2013] [Accepted: 08/07/2013] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Low levels of relative humidity are known to decrease the lifespan of mosquitoes. However, most current models of malaria transmission do not account for the effects of relative humidity on mosquito survival. In the Sahel, where relative humidity drops to levels <20% for several months of the year, we expect relative humidity to play a significant role in shaping the seasonal profile of mosquito populations. Here, we present a new formulation for Anopheles gambiae sensu lato (s.l.) mosquito survival as a function of temperature and relative humidity and investigate the effect of humidity on simulated mosquito populations. METHODS Using existing observations on relationships between temperature, relative humidity and mosquito longevity, we developed a new equation for mosquito survival as a function of temperature and relative humidity. We collected simultaneous field observations on temperature, wind, relative humidity, and anopheline mosquito populations for two villages from the Sahel region of Africa, which are presented in this paper. We apply this equation to the environmental data and conduct numerical simulations of mosquito populations using the Hydrology, Entomology and Malaria Transmission Simulator (HYDREMATS). RESULTS Relative humidity drops to levels that are uncomfortable for mosquitoes at the end of the rainy season. In one village, Banizoumbou, water pools dried up and interrupted mosquito breeding shortly after the end of the rainy season. In this case, relative humidity had little effect on the mosquito population. However, in the other village, Zindarou, the relatively shallow water table led to water pools that persisted several months beyond the end of the rainy season. In this case, the decrease in mosquito survival due to relative humidity improved the model's ability to reproduce the seasonal pattern of observed mosquito abundance. CONCLUSIONS We proposed a new equation to describe Anopheles gambiae s.l. mosquito survival as a function of temperature and relative humidity. We demonstrated that relative humidity can play a significant role in mosquito population and malaria transmission dynamics. Future modeling work should account for these effects of relative humidity.
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Affiliation(s)
- Teresa K Yamana
- Massachusetts Institute of Technology, Room 48–207, 15 Vassar Street, Cambridge, MA 02139, USA
| | - Elfatih A B Eltahir
- Massachusetts Institute of Technology, Room 48–207, 15 Vassar Street, Cambridge, MA 02139, USA
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Lunde TM, Lindtjørn B. Cattle and climate in Africa: How climate variability has influenced national cattle holdings from 1961-2008. PeerJ 2013; 1:e55. [PMID: 23638393 PMCID: PMC3629083 DOI: 10.7717/peerj.55] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2013] [Accepted: 03/03/2013] [Indexed: 11/23/2022] Open
Abstract
The role of cattle in developing countries is as a source of high-quality food, as draft animals, and as a source of manure and fuel. Cattle represent important contribution to household incomes, and in drought prone areas they can act as an insurance against weather risk. So far, no studies have addressed how historical variations in temperature and rainfall have influenced cattle populations in Africa. The focus of this study is to assess the historical impact of climate variability on national cattle holdings. We reconstruct the cattle density and distribution for two time periods; 1955-1960 and 2000-2005. Based on estimates from FAO and official numbers, we generated a time series of cattle densities from 1961-2008, and compared these data with precipitation and temperature anomalies for the same period. We show that from 1961-2008 rainfall and temperature have been modulating, and occasionally controlling, the number of cattle in Africa.
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Affiliation(s)
- Torleif Markussen Lunde
- Bjerknes Centre for Climate Research, University of Bergen/Uni Research, Norway
- Centre for International Health, University of Bergen, Norway
| | - Bernt Lindtjørn
- Centre for International Health, University of Bergen, Norway
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32
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Lunde TM, Balkew M, Korecha D, Gebre-Michael T, Massebo F, Sorteberg A, Lindtjørn B. A dynamic model of some malaria-transmitting anopheline mosquitoes of the Afrotropical region. II. Validation of species distribution and seasonal variations. Malar J 2013; 12:78. [PMID: 23442727 PMCID: PMC3653715 DOI: 10.1186/1475-2875-12-78] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2012] [Accepted: 02/18/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The first part of this study aimed to develop a model for Anopheles gambiae s.l. with separate parametrization schemes for Anopheles gambiae s.s. and Anopheles arabiensis. The characterizations were constructed based on literature from the past decades. This part of the study is focusing on the model's ability to separate the mean state of the two species of the An. gambiae complex in Africa. The model is also evaluated with respect to capturing the temporal variability of An. arabiensis in Ethiopia. Before conclusions and guidance based on models can be made, models need to be validated. METHODS The model used in this paper is described in part one (Malaria Journal 2013, 12:28). For the validation of the model, a data base of 5,935 points on the presence of An. gambiae s.s. and An. arabiensis was constructed. An additional 992 points were collected on the presence An. gambiae s.l.. These data were used to assess if the model could recreate the spatial distribution of the two species. The dataset is made available in the public domain. This is followed by a case study from Madagascar where the model's ability to recreate the relative fraction of each species is investigated. In the last section the model's ability to reproduce the temporal variability of An. arabiensis in Ethiopia is tested. The model was compared with data from four papers, and one field survey covering two years. RESULTS Overall, the model has a realistic representation of seasonal and year to year variability in mosquito densities in Ethiopia. The model is also able to describe the distribution of An. gambiae s.s. and An. arabiensis in sub-Saharan Africa. This implies this model can be used for seasonal and long term predictions of changes in the burden of malaria. Before models can be used to improving human health, or guide which interventions are to be applied where, there is a need to understand the system of interest. Validation is an important part of this process. It is also found that one of the main mechanisms separating An. gambiae s.s. and An. arabiensis is the availability of hosts; humans and cattle. Climate play a secondary, but still important, role.
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Affiliation(s)
- Torleif M Lunde
- Centre for International Health, University of Bergen, Bergen, Norway.
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Lunde TM, Bayoh MN, Lindtjørn B. How malaria models relate temperature to malaria transmission. Parasit Vectors 2013; 6:20. [PMID: 23332015 PMCID: PMC3598736 DOI: 10.1186/1756-3305-6-20] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2012] [Accepted: 01/15/2013] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND It is well known that temperature has a major influence on the transmission of malaria parasites to their hosts. However, mathematical models do not always agree about the way in which temperature affects malaria transmission. METHODS In this study, we compared six temperature dependent mortality models for the malaria vector Anopheles gambiae sensu stricto. The evaluation is based on a comparison between the models, and observations from semi-field and laboratory settings. RESULTS Our results show how different mortality calculations can influence the predicted dynamics of malaria transmission. CONCLUSIONS With global warming a reality, the projected changes in malaria transmission will depend on which mortality model is used to make such predictions.
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Affiliation(s)
- Torleif Markussen Lunde
- Bjerknes Centre for Climate Research, University of Bergen, Norway
- Centre for International Health, University of Bergen, Norway
- Bjerknes Centre for Climate Research, Uni Research, Norway
| | | | - Bernt Lindtjørn
- Centre for International Health, University of Bergen, Norway
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