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Duque C, Lubinda M, Matoba J, Sing’anga C, Stevenson J, Shields T, Shiff CJ. Impact of aerial humidity on seasonal malaria: an ecological study in Zambia. Malar J 2022; 21:325. [DOI: 10.1186/s12936-022-04345-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 10/27/2022] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Seasonal patterns of malaria cases in many parts of Africa are generally associated with rainfall, yet in the dry seasons, malaria transmission declines but does not always cease. It is important to understand what conditions support these periodic cases. Aerial moisture is thought to be important for mosquito survival and ability to forage, but its role during the dry seasons has not been well studied. During the dry season aerial moisture is minimal, but intermittent periods may arise from the transpiration of peri-domestic trees or from some other sources in the environment. These periods may provide conditions to sustain pockets of mosquitoes that become active and forage, thereby transmitting malaria. In this work, humidity along with other ecological variables that may impact malaria transmission have been examined.
Methods
Negative binomial regression models were used to explore the association between peri-domestic tree humidity and local malaria incidence. This was done using sensitive temperature and humidity loggers in the rural Southern Province of Zambia over three consecutive years. Additional variables including rainfall, temperature and elevation were also explored.
Results
A negative binomial model with no lag was found to best fit the malaria cases for the full year in the evaluated sites of the Southern Province of Zambia. Local tree and granary night-time humidity and temperature were found to be associated with local health centre-reported incidence of malaria, while rainfall and elevation did not significantly contribute to this model. A no lag and one week lag model for the dry season alone also showed a significant effect of humidity, but not temperature, elevation, or rainfall.
Conclusion
The study has shown that throughout the dry season, periodic conditions of sustained humidity occur that may permit foraging by resting mosquitoes, and these periods are associated with increased incidence of malaria cases. These results shed a light on conditions that impact the survival of the common malaria vector species, Anopheles arabiensis, in arid seasons and suggests how they emerge to forage when conditions permit.
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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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Weeraratne TC, Karunaratne SHPP, Reimer L, de Silva WAPP, Wondji CS. Use of transcriptional age grading technique to determine the chronological age of Sri Lankan Aedes aegypti and Aedes albopictus females. Parasit Vectors 2021; 14:493. [PMID: 34565445 PMCID: PMC8474866 DOI: 10.1186/s13071-021-04994-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 09/08/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Aedes aegypti and Ae. albopictus are important vectors of human diseases such as dengue, chikungunya, and zika. In Sri Lanka, they have been responsible for transmitting dengue virus. One of the most important parameters influencing the likelihood of arbovirus transmission is the age structure of the mosquito population. However, mosquito age is difficult to measure with accuracy. This study aims to construct multivariate calibration models using the transcriptional abundance of three age-responsive genes: Ae15848 (calcium-binding protein), Ae8505 (structural component of cuticle), and Ae4274 (fizzy cell cycle/cell division cycle 20). METHODS The transcriptional age-grading technique was applied to determine the chronological age of Ae. aegypti and Ae. albopictus female mosquito populations from Sri Lanka using the age-responsive genes Ae15848, Ae8505, and Ae4274. Furthermore, Ae. aegypti samples obtained from colonies reared at two temperatures (23 and 27 °C) were used to investigate the influence of temperature on this age-grading technique. Expression levels of these three genes were quantified using reverse transcription qualitative PCR (qRT-PCR), and results were normalized against the housekeeping gene ribosomal gene S17 (RpS17). RESULTS The expression of Ae15848 and Ae8505 decreased with the age of mosquitoes and showed the most significant and consistent change while expression of Ae4274 increased with age. The multivariate calibration models showed > 80% correlation between expression of these age-responsive genes and the age of female mosquitoes at both temperatures. At 27 °C the accuracy of age predictions using the models was 2.19 (± 1.66) days and 2.58 (± 2.06) days for Ae. aegypti and Ae. albopictus females, respectively. The accuracy of the model for Ae. aegypti at 23 °C was 3.42 (± 2.74) days. CONCLUSIONS An adult rearing temperature difference of 4 °C (23-27 °C) did not significantly affect the age predictions. The calibration models created during this study could be successfully used to estimate the age of wild Ae. aegypti and Ae. albopictus mosquitoes from Sri Lanka.
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Affiliation(s)
| | | | - Lisa Reimer
- Vector Biology Department, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK
| | | | - Charles S Wondji
- Vector Biology Department, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK.,Medical Entomology Department, Centre for Research in Infectious Diseases (CRID), Yaoundé, Cameroon
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4
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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: 16] [Impact Index Per Article: 2.7] [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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Kyalo D, Amratia P, Mundia CW, Mbogo CM, Coetzee M, Snow RW. A geo-coded inventory of anophelines in the Afrotropical Region south of the Sahara: 1898-2016. Wellcome Open Res 2017; 2:57. [PMID: 28884158 PMCID: PMC5558104 DOI: 10.12688/wellcomeopenres.12187.1] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/24/2017] [Indexed: 11/20/2022] Open
Abstract
Background: Understanding the distribution of anopheline vectors of malaria is an important prelude to the design of national malaria control and elimination programmes. A single, geo-coded continental inventory of anophelines using all available published and unpublished data has not been undertaken since the 1960s. Methods: We have searched African, European and World Health Organization archives to identify unpublished reports on anopheline surveys in 48 sub-Saharan Africa countries. This search was supplemented by identification of reports that formed part of post-graduate theses, conference abstracts, regional insecticide resistance databases and more traditional bibliographic searches of peer-reviewed literature. Finally, a check was made against two recent repositories of dominant malaria vector species locations ( circa 2,500). Each report was used to extract information on the survey dates, village locations (geo-coded to provide a longitude and latitude), sampling methods, species identification methods and all anopheline species found present during the survey. Survey records were collapsed to a single site over time. Results: The search strategy took years and resulted in 13,331 unique, geo-coded survey locations of anopheline vector occurrence between 1898 and 2016. A total of 12,204 (92%) sites reported the presence of 10 dominant vector species/sibling species; 4,473 (37%) of these sites were sampled since 2005. 4,442 (33%) sites reported at least one of 13 possible secondary vector species; 1,107 (25%) of these sites were sampled since 2005. Distributions of dominant and secondary vectors conform to previous descriptions of the ecological ranges of these vectors. Conclusion: We have assembled the largest ever geo-coded database of anophelines in Africa, representing a legacy dataset for future updating and identification of knowledge gaps at national levels. The geo-coded database is available on Harvard Dataverse as a reference source for African national malaria control programmes planning their future control and elimination strategies.
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Affiliation(s)
- David Kyalo
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Punam Amratia
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Clara W Mundia
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Charles M Mbogo
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya
| | - Maureen Coetzee
- Centre for Emerging, Zoonotic & Parasitic Diseases, National Institute for Communicable Diseases, Johannesburg, South Africa.,Wits Research Institute for Malaria, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Robert W Snow
- Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya.,Centre for Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
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Belay DB, Kifle YG, Goshu AT, Gran JM, Yewhalaw D, Duchateau L, Frigessi A. Joint Bayesian modeling of time to malaria and mosquito abundance in Ethiopia. BMC Infect Dis 2017; 17:415. [PMID: 28606100 PMCID: PMC5467264 DOI: 10.1186/s12879-017-2496-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 05/28/2017] [Indexed: 11/26/2022] Open
Abstract
Background This paper studies the effect of mosquito abundance and malaria incidence in the last 3 weeks, and their interaction, on the hazard of time to malaria in a previously studied cohort of children in Ethiopia. Methods We model the mosquito abundance and time to malaria data jointly in a Bayesian framework. Results We found that the interaction of mosquito abundance and incidence plays a prominent role on malaria risk. We quantify and compare relative risks of various factors, and determine the predominant role of the interaction between incidence and mosquito abundance in describing malaria risk. Seasonal rain patterns, distance to a water source of the households, temperature and relative humidity are all significant in explaining mosquito abundance, and through this affect malaria risk. Conclusion Analyzing jointly the time to malaria data and the mosquito abundance allows a precise comparison of factors affecting the spread of malaria. The effect of the interaction between mosquito abundances and local presence of malaria parasites has an important effect on the hazard of time to malaria, beyond abundance alone. Each additional one km away from the dam gives an average reduction of malaria relative risk of 5.7%. The importance of the interaction between abundance and incidence leads to the hypothesis that preventive intervention could advantageously target the infectious population, in addition to mosquito control, which is the typical intervention today.
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Affiliation(s)
- Denekew Bitew Belay
- School of Mathematical and Statistical Sciences, College of Natural and Computational Science, Hawassa University, Hawassa, Ethiopia.
| | - Yehenew Getachew Kifle
- Department of Statistics and Operations Research, University of Limpopo, Limpopo, South Africa
| | - Ayele Taye Goshu
- School of Mathematical and Statistical Sciences, College of Natural and Computational Science, Hawassa University, Hawassa, Ethiopia
| | - Jon Michael Gran
- Oslo Center for Biostatistics and Epidemiology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Delenasaw Yewhalaw
- Department of Medical Laboratory Sciences and Pathology, College of Health Sciences, Jimma University, Jimma, Ethiopia
| | - Luc Duchateau
- Department of Comparative Physiology and Biometrics, Ghent University, Ghent, Belgium
| | - Arnoldo Frigessi
- Oslo Center for Biostatistics and Epidemiology, University of Oslo and Oslo University Hospital, Oslo, Norway
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Abiodun GJ, Witbooi P, Okosun KO. Modeling and analyzing the impact of temperature and rainfall on mosquito population dynamics over Kwazulu-Natal, South Africa. INT J BIOMATH 2017. [DOI: 10.1142/s1793524517500553] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Malaria parasites are strongly dependent on Anopheles mosquitoes for transmission; for this reason, mosquito population dynamics are a crucial determinant of malaria risk. However, temperature and rainfall play a significant role in both aquatic and adult stages of the Anopheles. Consequently, it is important to understand the biology of malaria vector mosquitoes in the study of malaria transmission. In this study, we develop a climate-based, ordinary-differential-equation model to analyze how rainfall and temperature determine mosquito population size. In the model, we consider in detail the influence of ambient temperature on gonotrophic and sporogonic cycles over Amajuba District, Kwazulu-Natal Province, South Africa. In particular, we further use the model to simulate the spatial distribution of the mosquito biting rate over the study region. Our results reflect high seasonality of the population of An. gambiae over the region and also demonstrate the influence of climatic factors on the mosquito population dynamics.
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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
| | - 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, Vanderbijlpark, Andries Potgieter Blvrd-1900, Republic of South Africa
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Christiansen-Jucht C, Parham PE, Saddler A, Koella JC, Basáñez MG. Temperature during larval development and adult maintenance influences the survival of Anopheles gambiae s.s. Parasit Vectors 2014; 7:489. [PMID: 25367091 PMCID: PMC4236470 DOI: 10.1186/s13071-014-0489-3] [Citation(s) in RCA: 68] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2014] [Accepted: 10/13/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Malaria transmission depends on vector life-history parameters and population dynamics, and particularly on the survival of adult Anopheles mosquitoes. These dynamics are sensitive to climatic and environmental factors, and temperature is a particularly important driver. Data currently exist on the influence of constant and fluctuating adult environmental temperature on adult Anopheles gambiae s.s. survival and on the effect of larval environmental temperature on larval survival, but none on how larval temperature affects adult life-history parameters. METHODS Mosquito larvae and pupae were reared individually at different temperatures (23 ± 1°C, 27 ± 1°C, 31 ± 1°C, and 35 ± 1°C), 75 ± 5% relative humidity. Upon emergence into imagoes, individual adult females were either left at their larval temperature or placed at a different temperature within the range above. Survival was monitored every 24 hours and data were analysed using non-parametric and parametric methods. The Gompertz distribution fitted the survivorship data better than the gamma, Weibull, and exponential distributions overall and was adopted to describe mosquito mortality rates. RESULTS Increasing environmental temperature during the larval stages decreased larval survival (p < 0.001). Increases of 4°C (from 23°C to 27°C, 27°C to 31°C, and 31°C to 35°C), 8°C (27°C to 35°C) and 12°C (23°C to 35°C) statistically significantly increased larval mortality (p < 0.001). Higher environmental temperature during the adult stages significantly lowered adult survival overall (p < 0.001), with increases of 4°C and 8°C significantly influencing survival (p < 0.001). Increasing the larval environment temperature also significantly increased adult mortality overall (p < 0.001): a 4°C increase (23°C to 27°C) did not significantly affect adult survival (p > 0.05), but an 8°C increase did (p < 0.05). The effect of a 4°C increase in larval temperature from 27°C to 31°C depended on the adult environmental temperature. The data also suggest that differences between the temperatures of the larval and adult environments affects adult mosquito survival. CONCLUSIONS Environmental temperature affects Anopheles survival directly during the juvenile and adult stages, and indirectly, since temperature during larval development significantly influences adult survival. These results will help to parameterise more reliable mathematical models investigating the potential impact of temperature and global warming on malaria transmission.
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Affiliation(s)
- Céline Christiansen-Jucht
- Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary's campus), Imperial College London, Norfolk Place, London, W2 1PG, UK.
| | - Paul E Parham
- Department of Public Health and Policy, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, L69 3GL, UK. .,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, UK.
| | - Adam Saddler
- Division of Biology, Faculty of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, SL5 2PZ, Berkshire, UK.
| | - Jacob C Koella
- Division of Biology, Faculty of Life Sciences, Imperial College London, Silwood Park Campus, Ascot, SL5 2PZ, Berkshire, UK. .,Present address : Faculté des Sciences, Institut de Biologie, Université de Neuchâtel, Rue Emile-Argand 11, CH-2000, Neuchâtel, Switzerland.
| | - María-Gloria Basáñez
- Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine (St Mary's campus), Imperial College London, Norfolk Place, London, W2 1PG, UK.
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Maliti D, Ranson H, Magesa S, Kisinza W, Mcha J, Haji K, Killeen G, Weetman D. Islands and stepping-stones: comparative population structure of Anopheles gambiae sensu stricto and Anopheles arabiensis in Tanzania and implications for the spread of insecticide resistance. PLoS One 2014; 9:e110910. [PMID: 25353688 PMCID: PMC4212992 DOI: 10.1371/journal.pone.0110910] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2014] [Accepted: 09/08/2014] [Indexed: 11/21/2022] Open
Abstract
Population genetic structures of the two major malaria vectors Anopheles gambiae s.s. and An. arabiensis, differ markedly across Sub-Saharan Africa, which could reflect differences in historical demographies or in contemporary gene flow. Elucidation of the degree and cause of population structure is important for predicting the spread of genetic traits such as insecticide resistance genes or artificially engineered genes. Here the population genetics of An. gambiae s.s. and An. arabiensis in the central, eastern and island regions of Tanzania were compared. Microsatellite markers were screened in 33 collections of female An. gambiae s.l., originating from 22 geographical locations, four of which were sampled in two or three years between 2008 and 2010. An. gambiae were sampled from six sites, An. arabiensis from 14 sites, and both species from two sites, with an additional colonised insectary sample of each species. Frequencies of the knock-down resistance (kdr) alleles 1014S and 1014F were also determined. An. gambiae exhibited relatively high genetic differentiation (average pairwise FST = 0.131), significant even between nearby samples, but without clear geographical patterning. In contrast, An. arabiensis exhibited limited differentiation (average FST = 0.015), but strong isolation-by-distance (Mantel test r = 0.46, p = 0.0008). Most time-series samples of An. arabiensis were homogeneous, suggesting general temporal stability of the genetic structure. An. gambiae populations from Dar es Salaam and Bagamoyo were found to have high frequencies of kdr 1014S (around 70%), with almost 50% homozygote but was at much lower frequency on Unguja Island, with no. An. gambiae population genetic differentiation was consistent with an island model of genetic structuring with highly restricted gene flow, contrary to An. arabiensis which was consistent with a stepping-stone model of extensive, but geographically-restricted gene flow.
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Affiliation(s)
- Deodatus Maliti
- Ifakara Health Institute, Environmental Health and Ecological Sciences Thematic Group, Ifakara, Morogoro, United Republic of Tanzania
- University of Glasgow, Institute of Biodiversity Animal Health and Comparative Medicine, Glasgow, Lancashire, United Kingdom
| | - Hilary Ranson
- Department of Vector Biology, Liverpool School of Tropical Medicine, Merseyside, Liverpool, United Kingdom
| | - Stephen Magesa
- RTI International, Global Health Division, Dar es Salaam, United Republic of Tanzania
| | - William Kisinza
- National Institute for Medical Research, Amani Research Center, Muheza, Tanga, United Republic of Tanzania
| | - Juma Mcha
- Zanzibar Malaria Elimination Programme, Unguja, Zanzibar, United Republic of Tanzania
| | - Khamis Haji
- Zanzibar Malaria Elimination Programme, Unguja, Zanzibar, United Republic of Tanzania
| | - Gerald Killeen
- Ifakara Health Institute, Environmental Health and Ecological Sciences Thematic Group, Ifakara, Morogoro, United Republic of Tanzania
- Department of Vector Biology, Liverpool School of Tropical Medicine, Merseyside, Liverpool, United Kingdom
| | - David Weetman
- Department of Vector Biology, Liverpool School of Tropical Medicine, Merseyside, Liverpool, United Kingdom
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10
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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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11
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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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