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Keegan SP, Pedersen AB, Fenton A. The impact of within-host coinfection interactions on between-host parasite transmission dynamics varies with spatial scale. Proc Biol Sci 2024; 291:20240103. [PMID: 38628126 PMCID: PMC11021925 DOI: 10.1098/rspb.2024.0103] [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: 01/14/2024] [Accepted: 03/18/2024] [Indexed: 04/19/2024] Open
Abstract
Within-host interactions among coinfecting parasites can have major consequences for individual infection risk and disease severity. However, the impact of these within-host interactions on between-host parasite transmission, and the spatial scales over which they occur, remain unknown. We developed and apply a novel spatially explicit analysis to parasite infection data from a wild wood mouse (Apodemus sylvaticus) population. We previously demonstrated a strong within-host negative interaction between two wood mouse gastrointestinal parasites, the nematode Heligmosomoides polygyrus and the coccidian Eimeria hungaryensis, using drug-treatment experiments. Here, we show this negative within-host interaction can significantly alter the between-host transmission dynamics of E. hungaryensis, but only within spatially restricted neighbourhoods around each host. However, for the closely related species E. apionodes, which experiments show does not interact strongly with H. polygyrus, we did not find any effect on transmission over any spatial scale. Our results demonstrate that the effects of within-host coinfection interactions can ripple out beyond each host to alter the transmission dynamics of the parasites, but only over local scales that likely reflect the spatial dimension of transmission. Hence there may be knock-on consequences of drug treatments impacting the transmission of non-target parasites, altering infection risks even for non-treated individuals in the wider neighbourhood.
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Affiliation(s)
- Shaun P. Keegan
- Department of Evolution, Ecology and Behaviour, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool L69 7ZB, UK
| | - Amy B. Pedersen
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FL, UK
| | - Andy Fenton
- Department of Evolution, Ecology and Behaviour, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool L69 7ZB, UK
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2
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Belluccini G, Lin Q, Williams B, Lou Y, Vatansever Z, López-García M, Lythe G, Leitner T, Romero-Severson E, Molina-París C. A story of viral co-infection, co-transmission and co-feeding in ticks: how to compute an invasion reproduction number. ARXIV 2024:arXiv:2403.15282v1. [PMID: 38562445 PMCID: PMC10983997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
With a single circulating vector-borne virus, the basic reproduction number incorporates contributions from tick-to-tick (co-feeding), tick-to-host and host-to-tick transmission routes. With two different circulating vector-borne viral strains, resident and invasive, and under the assumption that co-feeding is the only transmission route in a tick population, the invasion reproduction number depends on whether the model system of ordinary differential equations possesses the property of neutrality. We show that a simple model, with two populations of ticks infected with one strain, resident or invasive, and one population of co-infected ticks, does not have Alizon's neutrality property. We present model alternatives that are capable of representing the invasion potential of a novel strain by including populations of ticks dually infected with the same strain. The invasion reproduction number is analysed with the next-generation method and via numerical simulations.
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Affiliation(s)
- Giulia Belluccini
- T-6, Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, 87545, NM, USA
- School of Mathematics, University of Leeds, Leeds, LS2 9JT, UK
| | - Qianying Lin
- T-6, Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, 87545, NM, USA
| | | | - Yijun Lou
- Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Zati Vatansever
- Department of Parasitology, Faculty of Veterinary Medicine, Kafkas University, Kars, Turkey
| | | | - Grant Lythe
- School of Mathematics, University of Leeds, Leeds, LS2 9JT, UK
| | - Thomas Leitner
- T-6, Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, 87545, NM, USA
| | - Ethan Romero-Severson
- T-6, Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, 87545, NM, USA
| | - Carmen Molina-París
- T-6, Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, 87545, NM, USA
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3
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Else KJ, Keiser J, Holland CV, Grencis RK, Sattelle DB, Fujiwara RT, Bueno LL, Asaolu SO, Sowemimo OA, Cooper PJ. Whipworm and roundworm infections. Nat Rev Dis Primers 2020; 6:44. [PMID: 32467581 DOI: 10.1038/s41572-020-0171-3] [Citation(s) in RCA: 104] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/01/2020] [Indexed: 12/26/2022]
Abstract
Trichuriasis and ascariasis are neglected tropical diseases caused by the gastrointestinal dwelling nematodes Trichuris trichiura (a whipworm) and Ascaris lumbricoides (a roundworm), respectively. Both parasites are staggeringly prevalent, particularly in tropical and subtropical areas, and are associated with substantial morbidity. Infection is initiated by ingestion of infective eggs, which hatch in the intestine. Thereafter, T. trichiura larvae moult within intestinal epithelial cells, with adult worms embedded in a partially intracellular niche in the large intestine, whereas A. lumbricoides larvae penetrate the gut mucosa and migrate through the liver and lungs before returning to the lumen of the small intestine, where adult worms dwell. Both species elicit type 2 anti-parasite immunity. Diagnosis is typically based on clinical presentation (gastrointestinal symptoms and inflammation) and the detection of eggs or parasite DNA in the faeces. Prevention and treatment strategies rely on periodic mass drug administration (generally with albendazole or mebendazole) to at-risk populations and improvements in water, sanitation and hygiene. The effectiveness of drug treatment is very high for A. lumbricoides infections, whereas cure rates for T. trichiura infections are low. Novel anthelminthic drugs are needed, together with vaccine development and tools for diagnosis and assessment of parasite control in the field.
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Affiliation(s)
- Kathryn J Else
- Lydia Becker Institute for Immunology and Inflammation, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
| | - Jennifer Keiser
- Department of Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute, Basel, Switzerland.,University of Basel, Basel, Switzerland
| | - Celia V Holland
- Department of Zoology, School of Natural Sciences, Trinity College Dublin, Dublin, Ireland
| | - Richard K Grencis
- Lydia Becker Institute for Immunology and Inflammation, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - David B Sattelle
- Centre for Respiratory Biology, UCL Respiratory, Rayne Building, University College London, London, UK
| | - Ricardo T Fujiwara
- Department of Parasitology, Institute of Biological Sciences (ICB), Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Lilian L Bueno
- Department of Parasitology, Institute of Biological Sciences (ICB), Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Samuel O Asaolu
- Department of Zoology, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria
| | - Oluyomi A Sowemimo
- Department of Zoology, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria
| | - Philip J Cooper
- Institute of Infection and Immunity, St George's University of London, London, UK.,Facultad de Ciencias Medicas, de la Salud y la Vida, Universidad Internacional del Ecuador, Quito, Ecuador
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4
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Owada K, Lau CL, Leonardo L, Clements ACA, Yakob L, Nielsen M, Carabin H, Soares Magalhães RJ. Spatial distribution and populations at risk of A. lumbricoides and T. trichiura co-infections and infection intensity classes: an ecological study. Parasit Vectors 2018; 11:535. [PMID: 30285906 PMCID: PMC6171148 DOI: 10.1186/s13071-018-3107-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Accepted: 09/11/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Soil-transmitted helminth (STH) infections are highly prevalent in the Philippines. Mapping the prevalence and high-intensity of STH co-infections can help guide targeted intervention programmes to reduce morbidity, especially among vulnerable school-aged children. In this study, we aimed to predict the spatial distribution of the prevalence of Ascaris lumbricoides and Trichuris trichiura co-infection and infection intensity classes in the Philippines to identify populations most in need of interventions. METHODS Data on STH infections from 29,919 individuals during the nationwide parasitological survey in 2005 to 2007 were included in the analysis. To geographically predict the prevalence of A. lumbricoides and T. trichiura co-infections and infection intensity classes, Bayesian multinomial geostatistical models were built including age, sex, environmental variables and a geostatistical random effect. The number of individuals co-infected and belonging to each of the infection intensity classes in 2017 was forecast by combining our predictive prevalence maps with population density maps. RESULTS Our models showed that school-aged children (5-19 years) are most at risk of A. lumbricoides and T. trichiura co-infections and of moderate/high infection intensity compared to other age groups. We identified target provinces where the likelihood of STH-associated morbidity was highest: Luzon (Bulacan, Benguet, Cavite, Sorsogon, Metropolitan Manila, Pampanga and Rizal), the Visayas (Cebu, Iloilo, Leyte and Negros Occidental), and in Mindanao (Agusan Del Norte, Davao Del Sur, Davao Oriental, Lanao Del Sur, Maguindanao, Misamis Oriental, Sulu and Zamboanga Del Sur). Luzon had the highest estimated number of school-aged children with A. lumbricoides and T. trichiura co-infections (estimated total 89,400), followed by the Visayas (38,300) and Mindanao (20,200). CONCLUSIONS Our study provided epidemiological evidence to highlight national priority areas for controlling co-infections and high intensity infections in the Philippines. Our maps could assist more geographically targeted interventions to reduce the risk of STH-associated morbidity in the Philippines.
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Affiliation(s)
- Kei Owada
- School of Medicine, The University of Queensland, QLD, South Brisbane, Australia. .,Children's Health and Environment Program, Child Health Research Centre, The University of Queensland, QLD, South Brisbane, Australia.
| | - Colleen L Lau
- Children's Health and Environment Program, Child Health Research Centre, The University of Queensland, QLD, South Brisbane, Australia.,Research School of Population Health, Australian National University, ACT, Canberra, Australia
| | - Lydia Leonardo
- Department of Parasitology, College of Public Health, University of the Philippines Manila, Manila, Philippines
| | - Archie C A Clements
- Research School of Population Health, Australian National University, ACT, Canberra, Australia
| | - Laith Yakob
- Department of Disease Control, London School of Hygiene and Tropical Medicine, London, UK
| | - Mark Nielsen
- School of Psychology, The University of Queensland, QLD, St Lucia, Australia.,Faculty of Humanities, University of Johannesburg, Auckland Park, South Africa
| | - Hélène Carabin
- Department of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma, USA
| | - Ricardo J Soares Magalhães
- Children's Health and Environment Program, Child Health Research Centre, The University of Queensland, QLD, South Brisbane, Australia.,Spatial Epidemiology Laboratory, School of Veterinary Science, The University of Queensland, QLD, Gatton, Australia
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5
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Booth M, Clements A. Neglected Tropical Disease Control - The Case for Adaptive, Location-specific Solutions. Trends Parasitol 2018; 34:272-282. [PMID: 29500033 DOI: 10.1016/j.pt.2018.02.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2017] [Revised: 01/31/2018] [Accepted: 02/01/2018] [Indexed: 02/07/2023]
Abstract
The world is experiencing environmental and social change at an unprecedented rate, with the effects being felt at local, regional, and international scales. This phenomenon may disrupt interventions against neglected tropical diseases (NTDs) that operate on the basis of linear scaling and 'one-size-fits-all'. Here we argue that investment in field-based data collection and building modelling capacity is required; that it is important to consider unintended consequences of interventions; that inferences can be drawn from wildlife ecology; and that interventions should become more location-specific. Collectively, these ideas underpin the development of adaptive decision-support tools that are sufficiently flexible to address emerging issues within the Anthropocene.
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Affiliation(s)
- Mark Booth
- Faculty of Medical Sciences, Newcastle University, UK.
| | - Archie Clements
- Research School of Population Health, Australian National University, Australia
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6
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Li L, Wang CH, Wang SF, Li MT, Yakob L, Cazelles B, Jin Z, Zhang WY. Hemorrhagic fever with renal syndrome in China: Mechanisms on two distinct annual peaks and control measures. INT J BIOMATH 2018; 11:1850030. [DOI: 10.1142/s1793524518500304] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2023]
Abstract
Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by several serotypes of hantavirus and 90% of all reported HFRS cases occur in China. However, the dynamics of such outbreak, particularly the characteristics of two distinct annual peaks in China, are not well understood. Here, we investigate several of the biologically plausible causes for the peaks in monthly HFRS cases, and find that the key factor is the interplay between periodic transmission rates and rodent periodic birth rate. Analysis of dynamical model reveals that vaccination plays a significant role in the control of HFRS in China. Sensitive analysis of different interventions demonstrates that integrating rodent culling and environmental management with the current vaccination program is effective for HFRS control. Our results suggest that for diseases from animals to human beings, the features of both animals and humans beings should be taken into account in the control and prevention strategies.
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Affiliation(s)
- Li Li
- School of Computer and Information Technology, Shanxi University, Taiyuan, Shanxi 030006, P. R. China
- Science and Technology on Electronic Test and Measurement Laboratory, North University of China, Taiyuan 030051, P. R. China
- Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention, Shanxi University, Taiyuan, Shanxi 030006, P. R. China
| | - Cui-Hua Wang
- Complex Systems Research Center, Shanxi University, Taiyuan, Shanxi 030006, P. R. China
| | - Shi-Fu Wang
- Department of Children’s Medical Laboratory, Diagnosis Center Qilu Children’s Hospital of Shandong University, Jinan 250022, P. R. China
| | - Ming-Tao Li
- Complex Systems Research Center, Shanxi University, Taiyuan, Shanxi 030006, P. R. China
| | - Laith Yakob
- Department of Disease Control, London School of Hygiene and Tropical Medicine, London, UK
| | - Bernard Cazelles
- UMMISCO, UMI 209 IRD-UPMC, 93142 Bondy, France
- Eco-Evolutionary Mathematics, IBENS UMR 8197, ENS, Paris, France
| | - Zhen Jin
- Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention, Shanxi University, Taiyuan, Shanxi 030006, P. R. China
- Complex Systems Research Center, Shanxi University, Taiyuan, Shanxi 030006, P. R. China
| | - Wen-Yi Zhang
- Institute of Disease Control and Prevention, Academy of Military Medical Science, Beijing 100071, P. R. China
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7
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Prevalence and associated risk factors of Giardia duodenalis infection among school-going children in Nepal. Parasitol Res 2017; 117:287-293. [DOI: 10.1007/s00436-017-5706-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2017] [Accepted: 11/29/2017] [Indexed: 11/26/2022]
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8
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Furuya-Kanamori L, Liang S, Milinovich G, Soares Magalhaes RJ, Clements ACA, Hu W, Brasil P, Frentiu FD, Dunning R, Yakob L. Co-distribution and co-infection of chikungunya and dengue viruses. BMC Infect Dis 2016; 16:84. [PMID: 26936191 PMCID: PMC4776349 DOI: 10.1186/s12879-016-1417-2] [Citation(s) in RCA: 143] [Impact Index Per Article: 17.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2015] [Accepted: 02/07/2016] [Indexed: 01/08/2023] Open
Abstract
Background Chikungunya and dengue infections are spatio-temporally related. The current review aims to determine the geographic limits of chikungunya, dengue and the principal mosquito vectors for both viruses and to synthesise current epidemiological understanding of their co-distribution. Methods Three biomedical databases (PubMed, Scopus and Web of Science) were searched from their inception until May 2015 for studies that reported concurrent detection of chikungunya and dengue viruses in the same patient. Additionally, data from WHO, CDC and Healthmap alerts were extracted to create up-to-date global distribution maps for both dengue and chikungunya. Results Evidence for chikungunya-dengue co-infection has been found in Angola, Gabon, India, Madagascar, Malaysia, Myanmar, Nigeria, Saint Martin, Singapore, Sri Lanka, Tanzania, Thailand and Yemen; these constitute only 13 out of the 98 countries/territories where both chikungunya and dengue epidemic/endemic transmission have been reported. Conclusions Understanding the true extent of chikungunya-dengue co-infection is hampered by current diagnosis largely based on their similar symptoms. Heightened awareness of chikungunya among the public and public health practitioners in the advent of the ongoing outbreak in the Americas can be expected to improve diagnostic rigour. Maps generated from the newly compiled lists of the geographic distribution of both pathogens and vectors represent the current geographical limits of chikungunya and dengue, as well as the countries/territories at risk of future incursion by both viruses. These describe regions of co-endemicity in which lab-based diagnosis of suspected cases is of higher priority. Electronic supplementary material The online version of this article (doi:10.1186/s12879-016-1417-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Luis Furuya-Kanamori
- Research School of Population Health, Australian National University, Acton, ACT 2601, Australia.
| | - Shaohong Liang
- Environmental Health Institute, National Environment Agency, Singapore, 138667, Singapore.
| | - Gabriel Milinovich
- School of Public Health and Social Work, Queensland University of Technology, Kelvin Grove, QLD, 4059, Australia.
| | - Ricardo J Soares Magalhaes
- School of Veterinary Science, University of Queensland, Gatton, QLD, 4343, Australia. .,UQ Children's Health Research Centre, University of Queensland, South Brisbane, QLD, 4101, Australia.
| | - Archie C A Clements
- Research School of Population Health, Australian National University, Acton, ACT 2601, Australia.
| | - Wenbiao Hu
- School of Public Health and Social Work, Queensland University of Technology, Kelvin Grove, QLD, 4059, Australia.
| | - Patricia Brasil
- Instituto Nacional de Infectologia Evandro Chagas/ Fiocruz, Rio de Janeiro, Brazil.
| | - Francesca D Frentiu
- School of Biomedical Sciences and Institute for Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, QLD, 4059, Australia.
| | - Rebecca Dunning
- Formerly School of Biomedical Sciences, University of Queensland, St Lucia, QLD, 4072, Australia.
| | - Laith Yakob
- Department of Disease Control, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK.
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9
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Cohen C, Einav M, Hawlena H. Path analyses of cross-sectional and longitudinal data suggest that variability in natural communities of blood-associated parasites is derived from host characteristics and not interspecific interactions. Parasit Vectors 2015; 8:429. [PMID: 26286391 PMCID: PMC4545369 DOI: 10.1186/s13071-015-1029-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2015] [Accepted: 08/02/2015] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND The parasite composition of wild host individuals often impacts their behavior and physiology, and the transmission dynamics of pathogenic species thereby determines disease risk in natural communities. Yet, the determinants of parasite composition in natural communities are still obscure. In particular, three fundamental questions remain open: (1) what are the relative roles of host and environmental characteristics compared with direct interactions between parasites in determining the community composition of parasites? (2) do these determinants affect parasites belonging to the same guild and those belonging to different guilds in similar manners? and (3) can cross-sectional and longitudinal analyses work interchangeably in detecting community determinants? Our study was designed to answer these three questions in a natural community of rodents and their fleas, ticks, and two vector-borne bacteria. METHODS We sampled a natural population of Gerbillus andersoni rodents and their blood-associated parasites on two occasions. By combining path analysis and model selection approaches, we then explored multiple direct and indirect paths that connect (i) the environmental and host-related characteristics to the infection probability of a host by each of the four parasite species, and (ii) the infection probabilities of the four species by each other. RESULTS Our results suggest that the majority of paths shaping the blood-associated communities are indirect, mostly determined by host characteristics and not by interspecific interactions or environmental conditions. The exact effects of host characteristics on infection probability by a given parasite depend on its life history and on the method of sampling, in which the cross-sectional and longitudinal methods are complementary. CONCLUSIONS Despite the awareness of the need of ecological investigations into natural host-vector-parasite communities in light of the emergence and re-emergence of vector-borne diseases, we lack sampling methods that are both practical and reliable. Here we illustrated how comprehensive patterns can be revealed from observational data by applying path analysis and model selection approaches and combining cross-sectional and longitudinal analyses. By employing this combined approach on blood-associated parasites, we were able to distinguish between direct and indirect effects and to predict the causal relationships between host-related characteristics and the parasite composition over time and space. We concluded that direct interactions within the community play only a minor role in determining community composition relative to host characteristics and the life history of the community members.
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Affiliation(s)
- Carmit Cohen
- Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel.
| | - Monica Einav
- Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel.
| | - Hadas Hawlena
- Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel.
- Mitrani Department of Desert Ecology, Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion, Israel.
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10
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Wang S, Spear RC. Exploring the contribution of host susceptibility to epidemiological patterns of Schistosoma japonicum infection using an individual-based model. Am J Trop Med Hyg 2015; 92:1245-52. [PMID: 25870427 DOI: 10.4269/ajtmh.14-0691] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2014] [Accepted: 03/11/2015] [Indexed: 11/07/2022] Open
Abstract
We recently reported the analysis of epidemiological data suggesting variability in individual susceptibility to infection by Schistosoma japonicum among rural villagers who reside in Sichuan Province of southwestern China. By supplementing the data used in the earlier analysis from other studies we have reported from this region, we presented improved estimates of cercarial exposure, which in turn, result in stronger evidence of susceptibility. This analysis was conducted using an individual-based mathematical model (IBM) whose use was motivated by the nature and extent of field data from the low-transmission environments exemplified by one of our datasets and typical of the current situation in most endemic areas of China. In addition to individual susceptibility and water contact, the model includes stochastic aspects of cercarial exposure as well as of diagnostic procedures, the latter being particularly relevant to the low-transmission environment. The simulation studies show that, to produce key aspects of the epidemiological findings, the distribution of susceptibility ranges over several orders of magnitude and is highly right skewed. We found no compelling evidence that the distribution of susceptibility differed between the two populations that underlie both the epidemiological and simulation results.
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Affiliation(s)
- Shuo Wang
- Center for Occupational and Environmental Health, School of Public Health, University of California, Berkeley, California
| | - Robert C Spear
- Center for Occupational and Environmental Health, School of Public Health, University of California, Berkeley, California
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11
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Civitello DJ, Rohr JR. Disentangling the effects of exposure and susceptibility on transmission of the zoonotic parasite Schistosoma mansoni. J Anim Ecol 2014; 83:1379-86. [PMID: 24702134 DOI: 10.1111/1365-2656.12222] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2014] [Accepted: 03/24/2014] [Indexed: 11/27/2022]
Abstract
For all parasites, transmission is composed of two processes: host contact with parasites ('exposure') and risk of infection given such contact ('susceptibility'). Classic models, such as mass action (density-dependent) transmission, lump these processes together. However, separating these processes could enhance predictions for disease dynamics, especially for free-living parasites. Here, we outline three transmission models that partition exposure and susceptibility. Using data from a study of Schistosoma mansoni (trematode) infections in Biomphalaria glabrata snails, we competed these three models against four alternative models, including the mass action model (which lumps exposure and susceptibility). The models that separately accounted for exposure and susceptibility best predicted prevalence across the density gradients of hosts and parasites, outperforming all other models based on Akaike information criterion. When embedded into a dynamic epidemiological model, the exposure-explicit models all predicted lower equilibrium densities of infected snails and human-infectious cercariae. Thus, population-level epidemiological models that utilize the classic mass action transmission model might overestimate human risk of schistosomiasis. More generally, the presented approach for disentangling exposure and susceptibility can distinguish between behavioural and immunological resistance, identify mechanisms of 'disease dilution' and provide a more complete dissection of drivers of parasite transmission.
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Affiliation(s)
- David J Civitello
- Department of Integrative Biology, University of South Florida, 4202 E Fowler Ave, Tampa, FL, 33620, USA
| | - Jason R Rohr
- Department of Integrative Biology, University of South Florida, 4202 E Fowler Ave, Tampa, FL, 33620, USA
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12
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Yakob L, Soares Magalhães RJ, Gray DJ, Milinovich G, Wardrop N, Dunning R, Barendregt J, Bieri F, Williams GM, Clements ACA. Modelling parasite aggregation: disentangling statistical and ecological approaches. Int J Parasitol 2014; 44:339-42. [PMID: 24703868 DOI: 10.1016/j.ijpara.2014.02.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2014] [Revised: 02/25/2014] [Accepted: 02/26/2014] [Indexed: 11/30/2022]
Abstract
The overdispersion in macroparasite infection intensity among host populations is commonly simulated using a constant negative binomial aggregation parameter. We describe an alternative to utilising the negative binomial approach and demonstrate important disparities in intervention efficacy projections that can come about from opting for pattern-fitting models that are not process-explicit. We present model output in the context of the epidemiology and control of soil-transmitted helminths due to the significant public health burden imposed by these parasites, but our methods are applicable to other infections with demonstrable aggregation in parasite numbers among hosts.
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Affiliation(s)
- Laith Yakob
- The University of Queensland, School of Population Health, Brisbane, Qld, Australia.
| | | | - Darren J Gray
- The University of Queensland, School of Population Health, Brisbane, Qld, Australia
| | - Gabriel Milinovich
- The University of Queensland, School of Population Health, Brisbane, Qld, Australia
| | - Nicola Wardrop
- University of Southampton, Geography and Environment, Southampton, England, United Kingdom
| | - Rebecca Dunning
- The University of Queensland, School of Biomedical Sciences, St Lucia, Qld, Australia
| | - Jan Barendregt
- The University of Queensland, School of Population Health, Brisbane, Qld, Australia
| | - Franziska Bieri
- The University of Queensland, School of Population Health, Brisbane, Qld, Australia
| | - Gail M Williams
- The University of Queensland, School of Population Health, Brisbane, Qld, Australia
| | - Archie C A Clements
- The University of Queensland, School of Population Health, Brisbane, Qld, Australia
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Atkinson JAM, Williams GM, Yakob L, Clements ACA, Barnes TS, McManus DP, Yang YR, Gray DJ. Synthesising 30 years of mathematical modelling of Echinococcus transmission. PLoS Negl Trop Dis 2013; 7:e2386. [PMID: 24009786 PMCID: PMC3757076 DOI: 10.1371/journal.pntd.0002386] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2012] [Accepted: 07/15/2013] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Echinococcosis is a complex zoonosis that has domestic and sylvatic lifecycles, and a range of different intermediate and definitive host species. The complexities of its transmission and the sparse evidence on the effectiveness of control strategies in diverse settings provide significant challenges for the design of effective public health policy against this disease. Mathematical modelling is a useful tool for simulating control packages under locally specific transmission conditions to inform optimal timing and frequency of phased interventions for cost-effective control of echinococcosis. The aims of this review of 30 years of Echinococcus modelling were to discern the epidemiological mechanisms underpinning models of Echinococcus granulosus and E. multilocularis transmission and to establish the need to include a human transmission component in such models. METHODOLOGY/PRINCIPAL FINDINGS A search was conducted of all relevant articles published up until July 2012, identified from the PubMED, Web of Knowledge and Medline databases and review of bibliographies of selected papers. Papers eligible for inclusion were those describing the design of a new model, or modification of an existing mathematical model of E. granulosus or E. multilocularis transmission. A total of 13 eligible papers were identified, five of which described mathematical models of E. granulosus and eight that described E. multilocularis transmission. These models varied primarily on the basis of six key mechanisms that all have the capacity to modulate model dynamics, qualitatively affecting projections. These are: 1) the inclusion of a 'latent' class and/or time delay from host exposure to infectiousness; 2) an age structure for animal hosts; 3) the presence of density-dependent constraints; 4) accounting for seasonality; 5) stochastic parameters; and 6) inclusion of spatial and risk structures. CONCLUSIONS/SIGNIFICANCE This review discusses the conditions under which these mechanisms may be important for inclusion in models of Echinococcus transmission and proposes recommendations for the design of dynamic human models of transmission. Accounting for the dynamic behaviour of the Echinococcus parasites in humans will be key to predicting changes in the disease burden over time and to simulate control strategies that optimise public health impact.
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Affiliation(s)
- Jo-An M Atkinson
- School of Population Health, Infectious Disease Epidemiology Unit, University of Queensland, Brisbane, Australia.
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