Irrigation and Vector-Borne Disease Transmission
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Data-Driven Identification of Potential Zika Virus Vectors Michelle V Evans1,2*, Tad a Dallas1,3, Barbara a Han4, Courtney C Murdock1,2,5,6,7,8, John M Drake1,2,8
RESEARCH ARTICLE Data-driven identification of potential Zika virus vectors Michelle V Evans1,2*, Tad A Dallas1,3, Barbara A Han4, Courtney C Murdock1,2,5,6,7,8, John M Drake1,2,8 1Odum School of Ecology, University of Georgia, Athens, United States; 2Center for the Ecology of Infectious Diseases, University of Georgia, Athens, United States; 3Department of Environmental Science and Policy, University of California-Davis, Davis, United States; 4Cary Institute of Ecosystem Studies, Millbrook, United States; 5Department of Infectious Disease, University of Georgia, Athens, United States; 6Center for Tropical Emerging Global Diseases, University of Georgia, Athens, United States; 7Center for Vaccines and Immunology, University of Georgia, Athens, United States; 8River Basin Center, University of Georgia, Athens, United States Abstract Zika is an emerging virus whose rapid spread is of great public health concern. Knowledge about transmission remains incomplete, especially concerning potential transmission in geographic areas in which it has not yet been introduced. To identify unknown vectors of Zika, we developed a data-driven model linking vector species and the Zika virus via vector-virus trait combinations that confer a propensity toward associations in an ecological network connecting flaviviruses and their mosquito vectors. Our model predicts that thirty-five species may be able to transmit the virus, seven of which are found in the continental United States, including Culex quinquefasciatus and Cx. pipiens. We suggest that empirical studies prioritize these species to confirm predictions of vector competence, enabling the correct identification of populations at risk for transmission within the United States. *For correspondence: mvevans@ DOI: 10.7554/eLife.22053.001 uga.edu Competing interests: The authors declare that no competing interests exist. -
Spatial Distribution and Seasonal Fluctuation of Mosquitoes in Dhaka
International Journal of Fauna and Biological Studies 2013; 1 (1): 42-46 ISSN 2347-2677 IJFBS 2013; 1 (1): 42-46 Spatial Distribution and Seasonal Fluctuation of Mosquitoes in © 2013 AkiNik Publications Dhaka City Received: 17-9-2013 Accepted: 27-9-2013 Md. Rezaul Karim, Md. Muzahidul Islam, Md. Sheik Farid, Md. Abdur Rashid*, Tangin Akter, Humayun Reza Khan Md. Rezaul Karim Department of Zoology, University of Dhaka, Dhaka- ABSTRACT In an entomological study conducted from March 2011 to February 2012), mosquito larvae and adults 1000, Bangladesh were collected from different breeding sites viz. drains, coconut barks, tree holes, lakes, artificial water Md. Muzahidul Islam containers and tubs in Dhaka city utilizing long aquatic nets and sweeping nets. Altogether, 3487 Department of Zoology, mosquitoes belonging to 13 species of 4 genera namely Culex (7), Mansonia (3), Aedes (2) and Armigeres (1) were sampled, all of which were under the family Culicidae. Among the collected University of Dhaka, Dhaka- mosquitoes Cx. quinquefasciatus (29%) showed the highest abundance followed by Cx. vishnui (23%), 1000, Bangladesh Cx. tritaeniorhynchus (14%), Cx. gelidus (6%), Cx. fatigans (5%), Cx. fuscocephala (5%) , Cx. hutchinsoni (5%), Mn. annulifera (3%), Mn. uniformis (2%), Mn. indiana (2%), Ae. aegypti (2%), Ae. Md. Sheik Farid albopictus (2%) and Ar. subalbatus (1%). Maximum number of species were found in Osmani Uddan Department of Zoology, (12, n = 750) followed by Old Dhaka (11, n = 1648), Sohrawardi Uddan (9, n = 516) and Fullbaria Bus University of Dhaka, Dhaka- Station (7, n = 573). Irrespective of species specific distribution, mosquitoes were found abundantly in 1000, Bangladesh August when the rainy water creates numerous temporary breeding grounds. -
An Assessment of the Water Quality in Major Streams of the Madu Ganga Catchment and Pollution Loads Draining Into the Madu Ganga from Its Own Catchment
An assessment of the water quality in major streams of the Madu Ganga catchment and pollution loads draining into the Madu Ganga from its own catchment A.A.D. Amarathunga* and N. Sureshkumar National Aquatic Resources Research and Development Agency (NARA), Crow Island, Colombo 15, Sri Lanka. Abstract The Madu Ganga Lagoon is located in the Southern Coast, Northwest of the city of Galle within the Galle District. The aim of this study was to evaluate the pollution status of the lagoon and the contribution of the land base pollutants from the catchment of the Madu Ganga. Selected water quality parameters were measured at monthly intervals at twelve sampling locations in the catchment. Certain parameters such as salinity (2.2 + 1.7 ppt), oil & grease (8.5 + 6.5 mg/L), total suspended solids (16.1 ± 12.3 mg/L), and turbidity (20.1 ± 12.5 NTU) are found to be elevated levels when compared with water quality standards. The study revealed that the Lenagala Ela brought a high nutrient load (426.7 kg/day) into Madu Ganga and Arawavilla Ela, Magala Ela and Bogaha Ela also contributed significantly. The highest nutrient loads were found with the onset of the Northeast Monsoon during November to January. The increase in nutrient loads is attributed to the fertilizers added to the soil with the commencement of the major paddy cultivation season. Keywords: Physico-chemical parameters, Madu Ganga, Water pollution, Nutrient load, Suspended sediment ^Corresponding author - Email: deeptha(s>nara.ac.lk, [email protected] Journal of the National Aquatic Resources Research and Development Agency, Vol. -
Annual Performance Report of the Ministry of Irrigation and Water
SO^a ^d S°rae/@^ ®g ^ 3 ^ 3 000 ^50da^u ^d ss^ 0 © ^ 0 0 m ® ®^3©i0^)^ SO §°0S SO^a & 0 i d ^ @ 0 ^ ^ iq t S i m g ^ u . Note Since original document prepared in English and translated to Sinhala/Tamil, in any discrepancy in words, English version shall be considered as correct. (g)fdlLJL| ^Lpso g^t)6H655TLD GlLonl^IiiJ60 ^ l u n r f l a a u u L l ® rflrhiaarnh / ^u51yp ^ d S lu j QLnuy51ffi(snjffi@ GIlditl^I 0uiLHTa«uuL_i_^rT6\) QLDrry5) 0uiLiiTuiJ6b 6j^rTeaQ ^rT0 (jprrswsrun@ ffimS55TLJULll_rT6\) ^rti]<£l6\)U Ljlp^l ff[fllUrT6O TQ ^6OT ffi0 ^LJU @ LD Message from the Secretary I am happy to present the Performance Report of the Ministry of Irrigation and Water Resources Management for the year 2011, having forged ahead to fulfill the mission and objectives of the Ministry, in the subjects and functions pertaining to the irrigation and water sub sectors. The year under review was eventful and we were able to take many progressive steps that will steer this sector to be more productive to serve the nation in the coming years. The capital investment programme of the Ministry had a workload of approximately Rs 20,000 million. This was a heavy development programme. We were on the path to achieve good progress, in spite of floods occurred in the beginning of the year and other constraints that had to be overcome during implementation. Steps were taken to remedy constraints such as staff shortages that existed, by new recruitments to the certain skilled technical grades but the shortage still prevails by large especially in the grades of Engineers, Engineering Assistants and other technical categories, which is being addressed by way of restructuring institutions, reviewing schemes of recruitments etc. -
The Government of the Democratic
THE GOVERNMENT OF THE DEMOCRATIC SOCIALIST REPUBLIC OF SRI LANKA FINANCIAL STATEMENTS OF THE GOVERNMENT FOR THE YEAR ENDED 31ST DECEMBER 2019 DEPARTMENT OF STATE ACCOUNTS GENERAL TREASURY COLOMBO-01 TABLE OF CONTENTS Page No. 1. Note to Readers 1 2. Statement of Responsibility 2 3. Statement of Financial Performance for the Year ended 31st December 2019 3 4. Statement of Financial Position as at 31st December 2019 4 5. Statement of Cash Flow for the Year ended 31st December 2019 5 6. Statement of Changes in Net Assets / Equity for the Year ended 31st December 2019 6 7. Current Year Actual vs Budget 7 8. Significant Accounting Policies 8-12 9. Time of Recording and Measurement for Presenting the Financial Statements of Republic 13-14 Notes 10. Note 1-10 - Notes to the Financial Statements 15-19 11. Note 11 - Foreign Borrowings 20-26 12. Note 12 - Foreign Grants 27-28 13. Note 13 - Domestic Non-Bank Borrowings 29 14. Note 14 - Domestic Debt Repayment 29 15. Note 15 - Recoveries from On-Lending 29 16. Note 16 - Statement of Non-Financial Assets 30-37 17. Note 17 - Advances to Public Officers 38 18. Note 18 - Advances to Government Departments 38 19. Note 19 - Membership Fees Paid 38 20. Note 20 - On-Lending 39-40 21. Note 21 (Note 21.1-21.5) - Capital Contribution/Shareholding in the Commercial Public Corporations/State Owned Companies/Plantation Companies/ Development Bank (8568/8548) 41-46 22. Note 22 - Rent and Work Advance Account 47-51 23. Note 23 - Consolidated Fund 52 24. Note 24 - Foreign Loan Revolving Funds 52 25. -
Water Balance Variability Across Sri Lanka for Assessing Agricultural and Environmental Water Use W.G.M
Agricultural Water Management 58 (2003) 171±192 Water balance variability across Sri Lanka for assessing agricultural and environmental water use W.G.M. Bastiaanssena,*, L. Chandrapalab aInternational Water Management Institute (IWMI), P.O. Box 2075, Colombo, Sri Lanka bDepartment of Meteorology, 383 Bauddaloka Mawatha, Colombo 7, Sri Lanka Abstract This paper describes a new procedure for hydrological data collection and assessment of agricultural and environmental water use using public domain satellite data. The variability of the annual water balance for Sri Lanka is estimated using observed rainfall and remotely sensed actual evaporation rates at a 1 km grid resolution. The Surface Energy Balance Algorithm for Land (SEBAL) has been used to assess the actual evaporation and storage changes in the root zone on a 10- day basis. The water balance was closed with a runoff component and a remainder term. Evaporation and runoff estimates were veri®ed against ground measurements using scintillometry and gauge readings respectively. The annual water balance for each of the 103 river basins of Sri Lanka is presented. The remainder term appeared to be less than 10% of the rainfall, which implies that the water balance is suf®ciently understood for policy and decision making. Access to water balance data is necessary as input into water accounting procedures, which simply describe the water status in hydrological systems (e.g. nation wide, river basin, irrigation scheme). The results show that the irrigation sector uses not more than 7% of the net water in¯ow. The total agricultural water use and the environmental systems usage is 15 and 51%, respectively of the net water in¯ow. -
The Genus Pythium in Mainland China
菌物学报 [email protected] 8 April 2013, 32(增刊): 20-44 Http://journals.im.ac.cn Mycosystema ISSN1672-6472 CN11-5180/Q © 2013 IMCAS, all rights reserved. The genus Pythium in mainland China HO Hon-Hing* Department of Biology, State University of New York, New Paltz, New York 12561, USA Abstract: A historical review of studies on the genus Pythium in mainland China was conducted, covering the occurrence, distribution, taxonomy, pathogenicity, plant disease control and its utilization. To date, 64 species of Pythium have been reported and 13 were described as new to the world: P. acrogynum, P. amasculinum, P. b ai sen se , P. boreale, P. breve, P. connatum, P. falciforme, P. guiyangense, P. guangxiense, P. hypoandrum, P. kummingense, P. nanningense and P. sinensis. The dominant species is P. aphanidermatum causing serious damping off and rotting of roots, stems, leaves and fruits of a wide variety of plants throughout the country. Most of the Pythium species are pathogenic with 44 species parasitic on plants, one on the red alga, Porphyra: P. porphyrae, two on mosquito larvae: P. carolinianum and P. guiyangense and two mycoparasitic: P. nunn and P. oligandrum. In comparison, 48 and 28 species have been reported, respectively, from Taiwan and Hainan Island with one new species described in Taiwan: P. sukuiense. The prospect of future study on the genus Pythium in mainland China was discussed. Key words: Pythiaceae, taxonomy, Oomycetes, Chromista, Straminopila 中国大陆的腐霉属菌物 何汉兴* 美国纽约州立大学 纽约 新帕尔茨 12561 摘 要:综述了中国大陆腐霉属的研究进展,内容包括腐霉属菌物的发生、分布、分类鉴定、致病性、所致植物病 害防治及腐霉的利用等方面。至今,中国已报道的腐霉属菌物有 64 个种,其中有 13 个种作为世界新种进行了描述, 这 13 个新种分别为:顶生腐霉 Pythium acrogynum,孤雌腐霉 P. -
River Basins
APPENDIX I.I 122 River Basins Basin No Name of Basin Catchment Basin No. Name of Basin Catchment Area Sq. Km. Area Sq. Km 1. Kelani Ganga 2278 53. Miyangolla Ela 225 2. Bolgoda Lake 374 54. Maduru Oya 1541 3. Kaluganga 2688 55. Pulliyanpotha Aru 52 4. Bemota Ganga 6622 56. Kirimechi Odai 77 5. Madu Ganga 59 57. Bodigoda Aru 164 6. Madampe Lake 90 58. Mandan Aru 13 7. Telwatte Ganga 51 59. Makarachchi Aru 37 8. Ratgama Lake 10 60. Mahaweli Ganga 10327 9. Gin Ganga 922 61. Kantalai Basin Per Ara 445- 10. Koggala Lake 64 62. Panna Oya 69 11. Polwatta Ganga 233 12. Nilwala Ganga 960 63. Palampotta Aru 143 13. Sinimodara Oya 38 64. Pankulam Ara 382 14. Kirama Oya 223 65. Kanchikamban Aru 205 15. Rekawa Oya 755 66. Palakutti A/u 20 16. Uruhokke Oya 348 67. Yan Oya 1520 17. Kachigala Ara 220 68. Mee Oya 90 18. Walawe Ganga 2442 69. Ma Oya 1024 19. Karagan Oya 58 70. Churian A/u 74 20. Malala Oya 399 71. Chavar Aru 31 21. Embilikala Oya 59 72. Palladi Aru 61 22. Kirindi Oya 1165 73. Nay Ara 187 23. Bambawe Ara 79 74. Kodalikallu Aru 74 24. Mahasilawa Oya 13 75. Per Ara 374 25. Butawa Oya 38 76. Pali Aru 84 26. Menik Ganga 1272 27. Katupila Aru 86 77. Muruthapilly Aru 41 28. Kuranda Ara 131 78. Thoravi! Aru 90 29. Namadagas Ara 46 79. Piramenthal Aru 82 30. Karambe Ara 46 80. Nethali Aru 120 31. -
Diptera, Culicidae) of Cambodia Pierre-Olivier Maquart, Didier Fontenille, Nil Rahola, Sony Yean, Sébastien Boyer
Checklist of the mosquito fauna (Diptera, Culicidae) of Cambodia Pierre-Olivier Maquart, Didier Fontenille, Nil Rahola, Sony Yean, Sébastien Boyer To cite this version: Pierre-Olivier Maquart, Didier Fontenille, Nil Rahola, Sony Yean, Sébastien Boyer. Checklist of the mosquito fauna (Diptera, Culicidae) of Cambodia. Parasite, EDP Sciences, 2021, 28, pp.60. 10.1051/parasite/2021056. hal-03318784 HAL Id: hal-03318784 https://hal.archives-ouvertes.fr/hal-03318784 Submitted on 10 Aug 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Distributed under a Creative Commons Attribution| 4.0 International License Parasite 28, 60 (2021) Ó P.-O. Maquart et al., published by EDP Sciences, 2021 https://doi.org/10.1051/parasite/2021056 Available online at: www.parasite-journal.org RESEARCH ARTICLE OPEN ACCESS Checklist of the mosquito fauna (Diptera, Culicidae) of Cambodia Pierre-Olivier Maquart1,* , Didier Fontenille1,2, Nil Rahola2, Sony Yean1, and Sébastien Boyer1 1 Medical and Veterinary Entomology Unit, Institut Pasteur du Cambodge 5, BP 983, Blvd. Monivong, 12201 Phnom Penh, Cambodia 2 MIVEGEC, University of Montpellier, CNRS, IRD, 911 Avenue Agropolis, 34394 Montpellier, France Received 25 January 2021, Accepted 4 July 2021, Published online 10 August 2021 Abstract – Between 2016 and 2020, the Medical and Veterinary Entomology unit of the Institut Pasteur du Cambodge collected over 230,000 mosquitoes. -
List of Rivers of Sri Lanka
Sl. No Name Length Source Drainage Location of mouth (Mahaweli River 335 km (208 mi) Kotmale Trincomalee 08°27′34″N 81°13′46″E / 8.45944°N 81.22944°E / 8.45944; 81.22944 (Mahaweli River 1 (Malvathu River 164 km (102 mi) Dambulla Vankalai 08°48′08″N 79°55′40″E / 8.80222°N 79.92778°E / 8.80222; 79.92778 (Malvathu River 2 (Kala Oya 148 km (92 mi) Dambulla Wilpattu 08°17′41″N 79°50′23″E / 8.29472°N 79.83972°E / 8.29472; 79.83972 (Kala Oya 3 (Kelani River 145 km (90 mi) Horton Plains Colombo 06°58′44″N 79°52′12″E / 6.97889°N 79.87000°E / 6.97889; 79.87000 (Kelani River 4 (Yan Oya 142 km (88 mi) Ritigala Pulmoddai 08°55′04″N 81°00′58″E / 8.91778°N 81.01611°E / 8.91778; 81.01611 (Yan Oya 5 (Deduru Oya 142 km (88 mi) Kurunegala Chilaw 07°36′50″N 79°48′12″E / 7.61389°N 79.80333°E / 7.61389; 79.80333 (Deduru Oya 6 (Walawe River 138 km (86 mi) Balangoda Ambalantota 06°06′19″N 81°00′57″E / 6.10528°N 81.01583°E / 6.10528; 81.01583 (Walawe River 7 (Maduru Oya 135 km (84 mi) Maduru Oya Kalkudah 07°56′24″N 81°33′05″E / 7.94000°N 81.55139°E / 7.94000; 81.55139 (Maduru Oya 8 (Maha Oya 134 km (83 mi) Hakurugammana Negombo 07°16′21″N 79°50′34″E / 7.27250°N 79.84278°E / 7.27250; 79.84278 (Maha Oya 9 (Kalu Ganga 129 km (80 mi) Adam's Peak Kalutara 06°34′10″N 79°57′44″E / 6.56944°N 79.96222°E / 6.56944; 79.96222 (Kalu Ganga 10 (Kirindi Oya 117 km (73 mi) Bandarawela Bundala 06°11′39″N 81°17′34″E / 6.19417°N 81.29278°E / 6.19417; 81.29278 (Kirindi Oya 11 (Kumbukkan Oya 116 km (72 mi) Dombagahawela Arugam Bay 06°48′36″N -
Ecology and Infection Rates of Natural Vectors Of
ECOLOGY AND INFECTION RATES OF NATURAL VECTORS OF FILARIASIS IN TANAI-IINTAN, SOUTH KALIMANTAN (BORNEO), INDONESIA Soeroto ~tmosoedjono',~urnomo', Sutanti ~atiwa~anto', Harijani A. ~arwoto~,and Michael J. ~an~s' Data ekologi nyamuk vektor &n tingkat infeksi filana secam ahmi &n secam buatan telah diperokh a2ui perkebunan karet di Kalimantan Selatan, Indonesia. Berbagai macam cam penangkapan &lam kondki ekologi yang berbeda telah dipakai dalam pengumpulan 51 jenis nyamuk (N = 95.735). Pembedahan nyamuk, infeksi buatan dan identijikasi larva jiIanMamengikuti prosedur dan kunci yang sudah baku. Infeksi filaria Brugia, Breinlia dan Cardiofilaria secara alami ditemukan pada nyamuk Coquillettidia crassipes Dan' penelitian ini dapat dijelaskan hasil infeksi budan, kepadatan populasi nyamuk secara musiman dan perbandingan cam penangkapan nyamuk. INTRODUCTION forest at approximately 25 meters elevation (Fig. 2). ~h~majorit~of the human population In September 1978, a collaborative study on the estate (245 persons), comprised of was begun in Tanah Intan, South Kalimantan approximately 60% resettled Javanese and 40% (Borneo), Indonesia by the Indonesian Ministry indigenous Banjarnese, derived their livelihood of Health and the U.S. Naval Medical Research from tapping rubber. Before initial mass Unit No. 2, Detachment, Jakarta, in order to treatment with diethylcarbamazine citrate define the role of feral and domestic animals (~ilarzan~),the infection rate for Bnrgia malayi as reservoir hosts for human filarial pathogens. in this human population -
Meta-Analyses of the Proportion of Japanese Encephalitis Virus Infection in Vectors and Vertebrate Hosts Ana R.S
Oliveira et al. Parasites & Vectors (2017) 10:418 DOI 10.1186/s13071-017-2354-7 RESEARCH Open Access Meta-analyses of the proportion of Japanese encephalitis virus infection in vectors and vertebrate hosts Ana R.S. Oliveira1, Lee W. Cohnstaedt2, Erin Strathe3, Luciana Etcheverry Hernández1, D. Scott McVey2, José Piaggio4 and Natalia Cernicchiaro1* Abstract Background: Japanese encephalitis (JE) is a zoonosis in Southeast Asia vectored by mosquitoes infected with the Japanese encephalitis virus (JEV). Japanese encephalitis is considered an emerging exotic infectious disease with potential for introduction in currently JEV-free countries. Pigs and ardeid birds are reservoir hosts and play a major role on the transmission dynamics of the disease. The objective of the study was to quantitatively summarize the proportion of JEV infection in vectors and vertebrate hosts from data pertaining to observational studies obtained in a systematic review of the literature on vector and host competence for JEV, using meta-analyses. Methods: Data gathered in this study pertained to three outcomes: proportion of JEV infection in vectors, proportion of JEV infection in vertebrate hosts, and minimum infection rate (MIR) in vectors. Random-effects subgroup meta-analysis models were fitted by species (mosquito or vertebrate host species) to estimate pooled summary measures, as well as to compute the variance between studies. Meta-regression models were fitted to assess the association between different predictors and the outcomes of interest and to identify sources of heterogeneity among studies. Predictors included in all models were mosquito/vertebrate host species, diagnostic methods, mosquito capture methods, season, country/region, age category, and number of mosquitos per pool.