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2. Population Pharmacokinetics of the Antimalarial Amodiaquine: a Pooled Analysis To Optimize Dosing

Author

Ali, Ali Mohamed, Penny, Melissa, Smith, Thomas, Workman, Lesley, Sasi, Philip, Adjei, George O, Aweeka, Francesca, Kiechel, Jean-René, Jullien, Vincent, Rijken, Marcus, Mcgready, Rose, Mwesigwa, Julia, Kristensen, Kim, Stepniewska, Kasia, Tarning, Joel, Barnes, Karen, Denti, Paolo, Massougbodji, Achille, Gansané, Adama, Adeothy, Adicat, Aubouy, Agnès, Ouedraogo, Alphonse, Annerberg, Anna, Bruneel, Arnaud, Phyo, Aung Pyae, Win, Aye Kyi, Benakis, A., Goka, Bamenla, Gourmel, Bernard, Ogutu, Bernhards, Schramm, Birgit, McGee, Bryan, Morgan, Caroline, Obonyo, Charles, Mazinda, Charles, Parzy, D., Ashley, Elizabeth, Baudin, Elisabeth, Juma, Elizabeth, Comte, Eric, Ouedraogo, Esperance, Nosten, François, Sugnaux, F., Cottrell, Gilles, Dorsey, Grant, Carn, Gwenaelle, Kossou, Hortense, Amedome, Hyacinthe, Kalyango, Joan, Faucher, Jean-François, Jones, Joel, Simpson, Julie, Doritchamou, Justin, Kurtzhals, J., Pinoges, Loretxu, Hoegberg, Lotte, BERTAUX, L., Malaika, L. Tshilolo Muepu, Bergstrand, Martin, Alifrangis, Michael, Branger, Michel, Cot, Michel, Cammas, Mireille, Kamya, Moses, Day, Nicholas, White, Nicholas, Taudon, N., Rodrigues, Onike, Chotsiri, Palang, Valeh, Parastou, Houzé, Pascal, Deloron, Philippe, Guérin, Philippe, Rosenthal, Philip, Hsi, Poe, German, Polina, Singhasivanon, Pratap, Smith, Richard, Lwango, R., Sirima, Sodiomon, Parikh, Sunil, Alegre, S. Sese, Clark, Tamara, Sundaygar, Timothy, Drysdale, Troy, Taylor, Walter, Sinou, V., Zolia, Yah, Swiss Tropical and Public Health Institute [Basel], University of Basel (Unibas), Ifakara Health Institute, University of Cape Town, Muhimbili University of Health and Allied Sciences, University of Ghana, University of California, Drugs for Neglected Diseases Initiative, Service de Pharmacologie, Hôpital Européen George Pompidou, Université Paris Descartes, Paris, France, Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Mahidol University [Bangkok], University of Oxford [Oxford], London School of Hygiene & Tropical Medicine [Fajara, The Gambia], University of Antwerp (UA), Development DMPK-PKPD, Novo Nordisk, Copenhagen, Denmark, Univ Copenhagen, Fac Hlth & Med Sci, Novo Nordisk Fdn, Dis Syst Biol,Ctr Prot Res, Copenhagen, Denmark, and Partenaires INRAE-Partenaires INRAE

Subjects
pediatrics, dose optimization, malaria, [SDV.SP]Life Sciences [q-bio]/Pharmaceutical sciences, NONMEM
Abstract

International audience; Amodiaquine plus artesunate is the recommended antimalarial treatment in many countries where malaria is endemic. However, pediatric doses are largely based on a linear extrapolation from adult doses. We pooled data from previously published studies on the pharmacokinetics of amodiaquine, to optimize the dose across all age groups. Adults and children with uncomplicated malaria received daily weight-based doses of amodiaquine or artesunate-amodiaquine over 3 days. Plasma concentration-time profiles for both the parent drug and the metabolite were characterized using nonlinear mixed-effects modeling. Amodiaquine pharmacokinetics were adequately described by a two-compartment disposition model, with first-order elimination leading to the formation of desethylamodiaquine, which was best described by a three-compartment disposition model. Body size and age were the main covariates affecting amodiaquine clearance. After adjusting for the effect of weight, clearance rates for amodiaquine and desethylamodiaquine reached 50% of adult maturation at 2.8 months (95% confidence interval [CI], 1.5 to 3.7 months) and 3.9 months (95% CI, 2.6 to 5.3 months) after birth, assuming that the baby was born at term. Bioavailability was 22.4% (95% CI, 15.6 to 31.9%) lower at the start of treatment than during convalescence, which suggests a malaria disease effect. Neither the drug formulation nor the hemoglobin concentration had an effect on any pharmacokinetic parameters. Results from simulations showed that current manufacturer dosing recommendations resulted in low desethylamodiaquine exposure in patients weighing 8 kg, 15 to 17 kg, 33 to 35 kg, and >62 kg compared to that in a typical 50-kg patient. We propose possible optimized dosing regimens to achieve similar drug exposures among all age groups, which require further validation.

Published
2018
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3. Human candidate gene polymorphisms and risk of severe malaria in children in Kilifi, Kenya: a case-control association study

Author

Ndila, Carolyne M, Uyoga, Sophie, Macharia, Alexander W, Nyutu, Gideon, Peshu, Norbert, Ojal, John, Shebe, Mohammed, Awuondo, Kennedy O, Mturi, Neema, Tsofa, Benjamin, Sepúlveda, Nuno, Clark, Taane G, Band, Gavin, Clarke, Geraldine, Rowlands, Kate, Hubbart, Christina, Jeffreys, Anna, Kariuki, Silvia, Marsh, Kevin, Mackinnon, Margaret, Maitland, Kathryn, Kwiatkowski, Dominic P, Rockett, Kirk A, Williams, Thomas N, Abathina, Amadou, Abubakar, Ismaela, Achidi, Eric, Agbenyega, Tsiri, Aiyegbo, Mohammed, Akoto, Alex, Allen, Angela, Allen, Stephen, Amenga-Etego, Lucas, Amodu, Folakemi, Amodu, Olukemi, Anchang-Kimbi, Judith, Ansah, Nana, Ansah, Patrick, Ansong, Daniel, Antwi, Sampson, Anyorigiya, Thomas, Apinjoh, Tobias, Asafo-Agyei, Emmanuel, Asoala, Victor, Atuguba, Frank, Auburn, Sarah, Bah, Abdou, Bamba, Kariatou, Bancone, Germana, Barnwell, David, Barry, Abdoulaye, Bauni, Evasius, Besingi, Richard, Bojang, Kalifa, Bougouma, Edith, Bull, Susan, Busby, George, Camara, Abdoulie, Camara, Landing, Campino, Susana, Carter, Richard, Carucci, Dan, Casals-Pascual, Climent, Ceesay, Ndey, Ceesay, Pa, Chau, Tran, Chuong, Ly, Clark, Taane, Cole-Ceesay, Ramou, Conway, David, Cook, Katharine, Cook, Olivia, Cornelius, Victoria, Corran, Patrick, Correa, Simon, Cox, Sharon, Craik, Rachel, Danso, Bakary, Davis, Timothy, Day, Nicholas, Deloukas, Panos, Dembele, Awa, Devries, Jantina, Dewasurendra, Rajika, Diakite, Mahamadou, Diarra, Elizabeth, Dibba, Yaya, Diss, Andrea, Djimdé, Abdoulaye, Dolo, Amagana, Doumbo, Ogobara, Doyle, Alan, Drakeley, Chris, Drury, Eleanor, Duffy, Patrick, Dunstan, Sarah, Ebonyi, Augustine, Elhassan, Ahmed, Elhassan, Ibrahim, Elzein, Abier, Enimil, Anthony, Esangbedo, Pamela, Evans, Jennifer, Evans, Julie, Farrar, Jeremy, Fernando, Deepika, Fitzpatrick, Kathryn, Fullah, Janet, Garcia, Jacob, Ghansah, Anita, Gottleib, Michael, Green, Angie, Hart, Lee, Hennsman, Meike, Hien, Tran, Hieu, Nguyen, Hilton, Eliza, Hodgson, Abraham, Horstmann, Rolf, Hughes, Catherine, Hussein, Ayman, Hutton, Robert, Ibrahim, Muntaser, Ishengoma, Deus, Jaiteh, Jula, Jallow, Mariatou, Jallow, Muminatou, Jammeh, Kebba, Jasseh, Momodou, Jobarteh, Amie, Johnson, Kimberly, Joseph, Sarah, Jyothi, Dushyanth, Kachala, David, Kamuya, Dorcas, Kanyi, Haddy, Karunajeewa, Harin, Karunaweera, Nadira, Keita, Momodou, Kerasidou, Angeliki, Khan, Aja, Kivinen, Katja, Kokwaro, Gilbert, Konate, Amadou, Konate, Salimata, Koram, Kwadwo, Kwiatkowski, Dominic, Laman, Moses, Si, Le, Leffler, Ellen, Lemnge, Martha, Lin, Enmoore, Alioune, Ly, Macharia, Alexander, Macinnis, Bronwyn, Mai, Nguyen, Makani, Julie, Malangone, Cinzia, Mangano, Valentina, Manjurano, Alphaxard, Manneh, Lamin, Manning, Laurens, Manske, Magnus, Marsh, Vicki, Maslen, Gareth, Maxwell, Caroline, Mbunwe, Eric, Mccreight, Marilyn, Mead, Daniel, Mendy, Alieu, Mendy, Anthony, Mensah, Nathan, Michon, Pascal, Miles, Alistair, Miotto, Olivo, Modiano, David, Mohamed, Hiba, Molloy, Sile, Molyneux, Malcolm, Molyneux, Sassy, Moore, Mike, Moyes, Catherine, Mtei, Frank, Mtove, George, Mueller, Ivo, Mugri, Regina, Munthali, Annie, Mutabingwa, Theonest, Nadjm, Behzad, Ndi, Andre, Ndila, Carolyne, Newton, Charles, Niangaly, Amadou, Njie, Haddy, Njie, Jalimory, Njie, Madi, Njie, Malick, Njie, Sophie, Njiragoma, Labes, Nkrumah, Francis, Ntunthama, Neema, Nyika, Aceme, Nyirongo, Vysaul, O'Brien, John, Obu, Herbert, Oduro, Abraham, Ofori, Alex, Olaniyan, Subulade, Olaosebikan, Rasaq, Oluoch, Tom, Omotade, Olayemi, Oni, Olajumoke, Onykwelu, Emmanuel, Opi, Daniel, Orimadegun, Adebola, O'Riordan, Sean, Ouedraogo, Issa, Oyola, Samuel, Parker, Michael, Pearson, Richard, Pensulo, Paul, Phiri, Ajib, Phu, Nguyen, Pinder, Margaret, Pirinen, Matti, Plowe, Chris, Potter, Claire, Poudiougou, Belco, Puijalon, Odile, Quyen, Nguyen, Ragoussis, Ioannis, Ragoussis, Jiannis, Rasheed, Oba, Reeder, John, Reyburn, Hugh, Riley, Eleanor, Risley, Paul, Rockett, Kirk, Rodford, Joanne, Rogers, Jane, Rogers, William, Ruano-Rubio, Valentín, Sabally-Ceesay, Kumba, Sadiq, Abubacar, Saidy-Khan, Momodou, Saine, Horeja, Sakuntabhai, Anavaj, Sall, Abdourahmane, Sambian, David, Sambou, Idrissa, Sanjoaquin, Miguel, Shah, Shivang, Shelton, Jennifer, Siba, Peter, Silva, Nilupa, Simmons, Cameron, Simpore, Jaques, Singhasivanon, Pratap, Sinh, Dinh, Sirima, Sodiomon, Sirugo, Giorgio, Sisay-Joof, Fatoumatta, Sissoko, Sibiry, Small, Kerrin, Somaskantharajah, Elilan, Spencer, Chris, Stalker, Jim, Stevens, Marryat, Suriyaphol, Prapat, Sylverken, Justice, Taal, Bintou, Tall, Adama, Taylor, Terrie, Teo, Yik, Thai, Cao, Thera, Mahamadou, Titanji, Vincent, Toure, Ousmane, Troye-Blomberg, Marita, Usen, Stanley, Vanderwal, Aaron, Wangai, Hannah, Watson, Renee, Williams, Thomas, Wilson, Michael, Wrigley, Rebecca, Yafi, Clarisse, Yamoah, Lawrence, The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford, London School of Hygiene and Tropical Medicine (LSHTM), The Wellcome Trust Sanger Institute [Cambridge], St Mary's Hospital, Imperial College, TNW and MM are funded through awards from the Wellcome Trust (grants 091758 and 202800 [to TNW] and grant 088634 [to MM]) and DPK and TGC receive support from the Medical Research Council (grant G19/9 [to DPK] and grants MR/K000551/1, MR/M01360X/1, MR/N010469/1, and MC_PC_15103 [to TGC]). The research leading to these results received funding from the European Community's Seventh Framework Programme (FP7/2007-2013, under grant agreement 242095) and from the Medical Research Council (grant G0600718). MalariaGEN is supported by the Wellcome Trust (WT077383/Z/05/Z) and by the Foundation for the National Institutes of Health (grant 566) as part of the Bill & Melinda Gates' Grand Challenges in Global Health Initiative. The Resource Centre for Genomic Epidemiology of Malaria is supported by the Wellcome Trust (grant 090770/Z/09/Z). Support was also provided by the Medical Research Council (grant G0600718). The Wellcome Trust also provides core awards to the Wellcome Trust Centre for Human Genetics (grant 090532/Z/09/Z) and to the Wellcome Trust Sanger Institute (grant 098051). This work forms part of a larger collaboration with the MalariaGEN Consortium, whose members are listed at http://www.malariagen.net/projects/host/consortium-members. This paper is published with permission from the Director of the Kenya Medical Research Institute (KEMRI)., MalariaGEN Consortium (Anavaj Sakuntabhai), and European Project: 242095,EC:FP7:HEALTH,FP7-HEALTH-2009-single-stage,EVIMALAR(2009)

Subjects
Case-Control Studies, Child, Child, Preschool, Female, Gene Frequency, Genetic Predisposition to Disease, Humans, Kenya, Malaria, Male, Polymorphism, Genetic, Hematology, macromolecular substances, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Article, Genetic, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, parasitic diseases, [SDV.MP.PAR]Life Sciences [q-bio]/Microbiology and Parasitology/Parasitology, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Polymorphism, Preschool
Abstract

Summary Background Human genetic factors are important determinants of malaria risk. We investigated associations between multiple candidate polymorphisms—many related to the structure or function of red blood cells—and risk for severe Plasmodium falciparum malaria and its specific phenotypes, including cerebral malaria, severe malaria anaemia, and respiratory distress. Methods We did a case-control study in Kilifi County, Kenya. We recruited as cases children presenting with severe malaria to the high-dependency ward of Kilifi County Hospital. We included as controls infants born in the local community between Aug 1, 2006, and Sept 30, 2010, who were part of a genetics study. We tested for associations between a range of candidate malaria-protective genes and risk for severe malaria and its specific phenotypes. We used a permutation approach to account for multiple comparisons between polymorphisms and severe malaria. We judged p values less than 0·005 significant for the primary analysis of the association between candidate genes and severe malaria. Findings Between June 11, 1995, and June 12, 2008, 2244 children with severe malaria were recruited to the study, and 3949 infants were included as controls. Overall, 263 (12%) of 2244 children with severe malaria died in hospital, including 196 (16%) of 1233 with cerebral malaria. We investigated 121 polymorphisms in 70 candidate severe malaria-associated genes. We found significant associations between risk for severe malaria overall and polymorphisms in 15 genes or locations, of which most were related to red blood cells: ABO, ATP2B4, ARL14, CD40LG, FREM3, INPP4B, G6PD, HBA (both HBA1 and HBA2), HBB, IL10, LPHN2 (also known as ADGRL2), LOC727982, RPS6KL1, CAND1, and GNAS. Combined, these genetic associations accounted for 5·2% of the variance in risk for developing severe malaria among individuals in the general population. We confirmed established associations between severe malaria and sickle-cell trait (odds ratio [OR] 0·15, 95% CI 0·11–0·20; p=2·61 × 10−58), blood group O (0·74, 0·66–0·82; p=6·26 × 10−8), and –α3·7-thalassaemia (0·83, 0·76–0·90; p=2·06 × 10−6). We also found strong associations between overall risk of severe malaria and polymorphisms in both ATP2B4 (OR 0·76, 95% CI 0·63–0·92; p=0·001) and FREM3 (0·64, 0·53–0·79; p=3·18 × 10−14). The association with FREM3 could be accounted for by linkage disequilibrium with a complex structural mutation within the glycophorin gene region (comprising GYPA, GYPB, and GYPE) that encodes for the rare Dantu blood group antigen. Heterozygosity for Dantu was associated with risk for severe malaria (OR 0·57, 95% CI 0·49–0·68; p=3·22 × 10−11), as was homozygosity (0·26, 0·11–0·62; p=0·002). Interpretation Both ATP2B4 and the Dantu blood group antigen are associated with the structure and function of red blood cells. ATP2B4 codes for plasma membrane calcium-transporting ATPase 4 (the major calcium pump on red blood cells) and the glycophorins are ligands for parasites to invade red blood cells. Future work should aim at uncovering the mechanisms by which these polymorphisms can result in severe malaria protection and investigate the implications of these associations for wider health. Funding Wellcome Trust, UK Medical Research Council, European Union, and Foundation for the National Institutes of Health as part of the Bill & Melinda Gates Grand Challenges in Global Health Initiative.

Published
2018
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4. Additional file 1: Table S1. of Very high carriage of gametocytes in asymptomatic low-density Plasmodium falciparum and P. vivax infections in western Thailand

Author

Nguitragool, Wang, Mueller, Ivo, Chalermpon Kumpitak, Teerawat Saeseu, Sirasate Bantuchai, Ritthideach Yorsaeng, Surapon Yimsamran, Wanchai Maneeboonyang, Patiwat Sa-Angchai, Wutthichai Chaimungkun, Prasert Rukmanee, Supalarp Puangsa-Art, Nipon Thanyavanich, Koepfli, Cristian, Felger, Ingrid, Jetsumon Sattabongkot, and Singhasivanon, Pratap

Abstract

Performance of qPCR and qRT-PCR. The threshold cycles (CT) are shown for detection of plasmid standards at different copy numbers per reaction. The means and the standard errors of the mean (SEM) are shown for CT values used to determine the amplification efficiency (E) and r 2, with values in parenthesis excluded. Neg indicates no amplification. The limit of detection (red) is defined as the lowest copy number with >â 50% success rate. (DOCX 24Â kb)

Published
2017
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7. An analysis of health system resources in relation to pandemic response capacity in the Greater Mekong Subregion

Author

Hanvoravongchai, Piya, Chavez, Irwin, Rudge, James, Touch, Sok, Putthasri, Weerasak, Chau, Pham Ngoc, Phommasack, Bounlay, Singhasivanon, Pratap, Coker, Richard, Renseigné, Non, Faculty of Medicine, Chulalongkorn University, Faculty of Tropical Medicine, Mahidol University, Communicable Diseases Policy Research Group, London School of Hygiene & Tropical Medicine, Cambodia Ministry of Health, Department of Communicable Disease Control, International Health Policy Programme-Thailand, Ministry of Public Health, Vietnam Military Medical University, National Emerging Infectious Diseases Coordination Office, and Fa Ngoum Road

Subjects
Resource (biology), General Computer Science, Health geography, Business, Management and Accounting(all), Population, Resource distribution, Geographic Mapping, lcsh:Computer applications to medicine. Medical informatics, 03 medical and health sciences, 0302 clinical medicine, Surveys and Questionnaires, [SDV.SPEE] Life Sciences [q-bio]/Public Health and Epidemiology, Influenza, Human, Health care, Medical Staff, Hospital, Humans, Health system, 030212 general & internal medicine, Resource allocation, Socioeconomics, education, Pandemics, Asia, Southeastern, Health equity, 2. Zero hunger, Theil index, education.field_of_study, business.industry, Research, Surge Capacity, 1. No poverty, Public Health, Environmental and Occupational Health, Antivirals, Southeast Asia, General Business, Management and Accounting, 3. Good health, Geography, Resource mapping, lcsh:R858-859.7, Health Resources, business, Delivery of Health Care, Pandemic influenza, 030217 neurology & neurosurgery, Computer Science(all)
Abstract

Background There is increasing perception that countries cannot work in isolation to militate against the threat of pandemic influenza. In the Greater Mekong Subregion (GMS) of Asia, high socio-economic diversity and fertile conditions for the emergence and spread of infectious diseases underscore the importance of transnational cooperation. Investigation of healthcare resource distribution and inequalities can help determine the need for, and inform decisions regarding, resource sharing and mobilisation. Methods We collected data on healthcare resources deemed important for responding to pandemic influenza through surveys of hospitals and district health offices across four countries of the GMS (Cambodia, Lao PDR, Thailand, Vietnam). Focusing on four key resource types (oseltamivir, hospital beds, ventilators, and health workers), we mapped and analysed resource distributions at province level to identify relative shortages, mismatches, and clustering of resources. We analysed inequalities in resource distribution using the Gini coefficient and Theil index. Results Three quarters of the Cambodian population and two thirds of the Laotian population live in relatively underserved provinces (those with resource densities in the lowest quintile across the region) in relation to health workers, ventilators, and hospital beds. More than a quarter of the Thai population is relatively underserved for health workers and oseltamivir. Approximately one fifth of the Vietnamese population is underserved for beds and ventilators. All Cambodian provinces are underserved for at least one resource. In Lao PDR, 11 percent of the population is underserved by all four resource items. Of the four resources, ventilators and oseltamivir were most unequally distributed. Cambodia generally showed higher levels of inequalities in resource distribution compared to other countries. Decomposition of the Theil index suggests that inequalities result principally from differences within, rather than between, countries. Conclusions There is considerable heterogeneity in healthcare resource distribution within and across countries of the GMS. Most inequalities result from within countries. Given the inequalities, mismatches, and clustering of resources observed here, resource sharing and mobilization in a pandemic scenario could be crucial for more effective and equitable use of the resources that are available in the GMS.

Published
2012
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8. Additional file 1: Table S1. of Very high carriage of gametocytes in asymptomatic low-density Plasmodium falciparum and P. vivax infections in western Thailand

Author

Nguitragool, Wang, Mueller, Ivo, Chalermpon Kumpitak, Teerawat Saeseu, Sirasate Bantuchai, Ritthideach Yorsaeng, Surapon Yimsamran, Wanchai Maneeboonyang, Patiwat Sa-Angchai, Wutthichai Chaimungkun, Prasert Rukmanee, Supalarp Puangsa-Art, Nipon Thanyavanich, Koepfli, Cristian, Felger, Ingrid, Jetsumon Sattabongkot, and Singhasivanon, Pratap

Subjects
3. Good health
Abstract

Performance of qPCR and qRT-PCR. The threshold cycles (CT) are shown for detection of plasmid standards at different copy numbers per reaction. The means and the standard errors of the mean (SEM) are shown for CT values used to determine the amplification efficiency (E) and r 2, with values in parenthesis excluded. Neg indicates no amplification. The limit of detection (red) is defined as the lowest copy number with >â 50% success rate. (DOCX 24Â kb)

9. MOESM7 of The epidemiology of subclinical malaria infections in South-East Asia: findings from cross-sectional surveys in Thailand–Myanmar border areas, Cambodia, and Vietnam

Author

Imwong, Mallika, Nguyen, Thuy, Rupam Tripura, Peto, Tom, Lee, Sue, Khin Lwin, Preyanan Suangkanarat, Atthanee Jeeyapant, Benchawan Vihokhern, Klanarong Wongsaen, Hue, Dao, Dong, Le, Tam-Uyen Nguyen, Lubell, Yoel, Seidlein, Lorenz, Mehul Dhorda, Cholrawee Promnarate, Snounou, Georges, Benoit Malleret, Rénia, Laurent, Keereecharoen, Lilly, Singhasivanon, Pratap, Pasathorn Sirithiranont, Jem Chalk, Chea Nguon, Hien, Tran, Day, Nicholas, White, Nicholas, Dondorp, Arjen, and Francois Nosten

Subjects
3. Good health
Abstract

Additional file 7. Adjusted odds for being HVUSqPCR positive stratified by household, random effects modelling by country. In Cambodia the initial model included resident (0/1), anemia (mild, moderate, none), fever (defined as a temperature >37.5 °C) at presentation* (0/1), history of fever (0/1), sex, age group (

10. MOESM7 of The epidemiology of subclinical malaria infections in South-East Asia: findings from cross-sectional surveys in Thailand–Myanmar border areas, Cambodia, and Vietnam

Author

Imwong, Mallika, Nguyen, Thuy, Rupam Tripura, Peto, Tom, Lee, Sue, Khin Lwin, Preyanan Suangkanarat, Atthanee Jeeyapant, Benchawan Vihokhern, Klanarong Wongsaen, Hue, Dao, Dong, Le, Tam-Uyen Nguyen, Lubell, Yoel, Seidlein, Lorenz, Mehul Dhorda, Cholrawee Promnarate, Snounou, Georges, Benoit Malleret, Rénia, Laurent, Keereecharoen, Lilly, Singhasivanon, Pratap, Pasathorn Sirithiranont, Jem Chalk, Chea Nguon, Hien, Tran, Day, Nicholas, White, Nicholas, Dondorp, Arjen, and Francois Nosten

Subjects
3. Good health
Abstract

Additional file 7. Adjusted odds for being HVUSqPCR positive stratified by household, random effects modelling by country. In Cambodia the initial model included resident (0/1), anemia (mild, moderate, none), fever (defined as a temperature >37.5 °C) at presentation* (0/1), history of fever (0/1), sex, age group (

11. MOESM4 of The epidemiology of subclinical malaria infections in South-East Asia: findings from cross-sectional surveys in Thailandâ Myanmar border areas, Cambodia, and Vietnam

Author

Imwong, Mallika, Nguyen, Thuy, Rupam Tripura, Peto, Tom, Lee, Sue, Khin Lwin, Preyanan Suangkanarat, Atthanee Jeeyapant, Benchawan Vihokhern, Klanarong Wongsaen, Hue, Dao, Dong, Le, Tam-Uyen Nguyen, Lubell, Yoel, Seidlein, Lorenz, Mehul Dhorda, Cholrawee Promnarate, Snounou, Georges, Benoit Malleret, RĂŠnia, Laurent, Keereecharoen, Lilly, Singhasivanon, Pratap, Pasathorn Sirithiranont, Jem Chalk, Chea Nguon, Hien, Tran, Day, Nicholas, White, Nicholas, Dondorp, Arjen, and Francois Nosten

Subjects
3. Good health
Abstract

Additional file 4. The results of RDT, light microscopy, and HVUSqPCR in Cambodia, Thailand Myanmar border areas, and Vietnam (disaggregated by village).

12. MOESM1 of The epidemiology of subclinical malaria infections in South-East Asia: findings from cross-sectional surveys in Thailandâ Myanmar border areas, Cambodia, and Vietnam

Author

Imwong, Mallika, Nguyen, Thuy, Rupam Tripura, Peto, Tom, Lee, Sue, Khin Lwin, Preyanan Suangkanarat, Atthanee Jeeyapant, Benchawan Vihokhern, Klanarong Wongsaen, Hue, Dao, Dong, Le, Tam-Uyen Nguyen, Lubell, Yoel, Seidlein, Lorenz, Mehul Dhorda, Cholrawee Promnarate, Snounou, Georges, Benoit Malleret, RĂŠnia, Laurent, Keereecharoen, Lilly, Singhasivanon, Pratap, Pasathorn Sirithiranont, Jem Chalk, Chea Nguon, Hien, Tran, Day, Nicholas, White, Nicholas, Dondorp, Arjen, and Francois Nosten

Subjects
3. Good health
Abstract

Additional file 1: Table S1. Parasite prevalence in 12 villages along the Thailandâ Myanmar border. The villages are sorted by parasite prevalence. The four villages with the highest prevalence were selected for more exhaustive studies.

13. Additional file 1 of A randomized controlled trial of dihydroartemisinin-piperaquine, artesunate-mefloquine and extended artemether-lumefantrine treatments for malaria in pregnancy on the Thailand-Myanmar border

Author

Saito, Makoto, Carrara, Verena I., Gilder, Mary Ellen, Min, Aung Myat, Tun, Nay Win, Pimanpanarak, Mupawjay, Viladpai-nguen, Jacher, Paw, Moo Kho, Haohankhunnatham, Warat, Konghahong, Kamonchanok, Phyo, Aung Pyae, Chu, Cindy, Turner, Claudia, Lee, Sue J., Duanguppama, Jureeporn, Imwong, Mallika, Bancone, Germana, Proux, Stephane, Singhasivanon, Pratap, White, Nicholas J., Nosten, François, and McGready, Rose

Subjects
parasitic diseases, 3. Good health
Abstract

Additional file 1: S1 Table. Definition of primary efficacy endpoint by initial species. S2 Table. Dose of each compound given to the participants. S3 Table. The baseline characteristics of women with Plasmodium falciparum mono-infection. S4 Table. The baseline characteristics of women with Plasmodium vivax mono-infection. S5 Table. The baseline characteristics of patients with Plasmodium falciparum infection, including both P. falciparum mono-infection and co-infection of P. falciparum and Plasmodium vivax. S6 Table. Cumulative proportion of fever and parasite clearance of falciparum and vivax for each treatment arm among pregnant women with history of fever or documented fever at enrolment. S7 Table. Description of gametocyte carriage, congenital and placental malaria. S8 Table. Univariable and multivariable analyses of the risk of PCR-corrected treatment failure in pregnant women with uncomplicated falciparum malaria using a Cox proportional hazard model. S9 Table. Univariable and multivariable analyses on the risk of PCR-corrected treatment failure in pregnant women with uncomplicated falciparum malaria using a Cox proportional hazard model with Pfkelch13 mutations. S10 Table. Prevalence of symptoms before and after treatment. S11 Table. Description of pregnancy outcomes. S12 Table. Details of pregnant women who had miscarriage or stillbirth. S13 Table. Details of congenital abnormality and ICD-10 coding. S14 Table. Details of neonatal mortality. S15 Table. Univariable and multivariable linear regression analyses of the characteristics associated with gestational week at birth among those who had malaria in pregnancy. S16 Table. Univariable and multivariable linear regression analyses of the characteristics associated with SGA z-score (birthweight for gestational age and newborn sex at birth). S17 Table. Birth outcomes in pregnant women who had malaria and were enrolled in the first trimester. S1 Figure. Monthly number of pregnant women with malaria for each malaria species over the study period (from February 2010 to August 2016). S2 Figure. Kaplan-Meier survival curves for antimalarials in pregnancy: Panel a. recurrence of any malaria species, Panel b. Plasmodium falciparum PCR-corrected efficacy censoring intercalated Plasmodium vivax malaria, Panel c. P. falciparum PCR-uncorrected efficacy , and Panel d. P. vivax parasitaemia after P. falciparum mono-infection. S3 Figure. Kaplan-Meier survival curves for parasite clearance of Plasmodium falciparum (Panel a) or Plasmodium vivax (Panel b) for each treatment arm. S4 Figure. Fractional change in haematocrit from baseline during the follow-up for each species (Panel a) or treatment stratified by malaria species (Panel b).

14. MOESM2 of The epidemiology of subclinical malaria infections in South-East Asia: findings from cross-sectional surveys in Thailandâ Myanmar border areas, Cambodia, and Vietnam

Author

Imwong, Mallika, Nguyen, Thuy, Rupam Tripura, Peto, Tom, Lee, Sue, Khin Lwin, Preyanan Suangkanarat, Atthanee Jeeyapant, Benchawan Vihokhern, Klanarong Wongsaen, Hue, Dao, Dong, Le, Tam-Uyen Nguyen, Lubell, Yoel, Seidlein, Lorenz, Mehul Dhorda, Cholrawee Promnarate, Snounou, Georges, Benoit Malleret, RĂŠnia, Laurent, Keereecharoen, Lilly, Singhasivanon, Pratap, Pasathorn Sirithiranont, Jem Chalk, Chea Nguon, Hien, Tran, Day, Nicholas, White, Nicholas, Dondorp, Arjen, and Francois Nosten

Subjects
parasitic diseases, 3. Good health
Abstract

Additional file 2. Reasons why individuals were not included in the malaria surveys.

15. MOESM3 of The epidemiology of subclinical malaria infections in South-East Asia: findings from cross-sectional surveys in Thailandâ Myanmar border areas, Cambodia, and Vietnam

Author

Imwong, Mallika, Nguyen, Thuy, Rupam Tripura, Peto, Tom, Lee, Sue, Khin Lwin, Preyanan Suangkanarat, Atthanee Jeeyapant, Benchawan Vihokhern, Klanarong Wongsaen, Hue, Dao, Dong, Le, Tam-Uyen Nguyen, Lubell, Yoel, Seidlein, Lorenz, Mehul Dhorda, Cholrawee Promnarate, Snounou, Georges, Benoit Malleret, RĂŠnia, Laurent, Keereecharoen, Lilly, Singhasivanon, Pratap, Pasathorn Sirithiranont, Jem Chalk, Chea Nguon, Hien, Tran, Day, Nicholas, White, Nicholas, Dondorp, Arjen, and Francois Nosten

Subjects
parasitic diseases, 3. Good health
Abstract

Additional file 3. Study population characteristics in the malaria surveys (disaggregated by village).

16. Very high carriage of gametocytes in asymptomatic low-density Plasmodium falciparum and P. vivax infections in western Thailand

Author

Nguitragool, Wang, Mueller, Ivo, Kumpitak, Chalermpon, Saeseu, Teerawat, Bantuchai, Sirasate, Yorsaeng, Ritthideach, Yimsamran, Surapon, Maneeboonyang, Wanchai, Sa-Angchai, Patiwat, Chaimungkun, Wutthichai, Rukmanee, Prasert, Puangsa-Art, Supalarp, Thanyavanich, Nipon, Koepfli, Cristian, Felger, Ingrid, Sattabongkot, Jetsumon, and Singhasivanon, Pratap

Subjects
3. Good health

17. MOESM5 of The epidemiology of subclinical malaria infections in South-East Asia: findings from cross-sectional surveys in Thailandâ Myanmar border areas, Cambodia, and Vietnam

Author

Imwong, Mallika, Nguyen, Thuy, Rupam Tripura, Peto, Tom, Lee, Sue, Khin Lwin, Preyanan Suangkanarat, Atthanee Jeeyapant, Benchawan Vihokhern, Klanarong Wongsaen, Hue, Dao, Dong, Le, Tam-Uyen Nguyen, Lubell, Yoel, Seidlein, Lorenz, Mehul Dhorda, Cholrawee Promnarate, Snounou, Georges, Benoit Malleret, RĂŠnia, Laurent, Keereecharoen, Lilly, Singhasivanon, Pratap, Pasathorn Sirithiranont, Jem Chalk, Chea Nguon, Hien, Tran, Day, Nicholas, White, Nicholas, Dondorp, Arjen, and Francois Nosten

Subjects
parasitic diseases, 3. Good health
Abstract

Additional file 5. Sensitivity, specificity, positive predictive value and negative predictive value of RDTs and microscopy compared with HVUSqPCR species detection (disaggregated by village).

18. Additional file 1 of A randomized controlled trial of dihydroartemisinin-piperaquine, artesunate-mefloquine and extended artemether-lumefantrine treatments for malaria in pregnancy on the Thailand-Myanmar border

Author

Saito, Makoto, Carrara, Verena I., Gilder, Mary Ellen, Min, Aung Myat, Tun, Nay Win, Pimanpanarak, Mupawjay, Viladpai-nguen, Jacher, Paw, Moo Kho, Haohankhunnatham, Warat, Konghahong, Kamonchanok, Phyo, Aung Pyae, Chu, Cindy, Turner, Claudia, Lee, Sue J., Duanguppama, Jureeporn, Imwong, Mallika, Bancone, Germana, Proux, Stephane, Singhasivanon, Pratap, White, Nicholas J., Nosten, François, and McGready, Rose

Subjects
parasitic diseases, 3. Good health
Abstract

Additional file 1: S1 Table. Definition of primary efficacy endpoint by initial species. S2 Table. Dose of each compound given to the participants. S3 Table. The baseline characteristics of women with Plasmodium falciparum mono-infection. S4 Table. The baseline characteristics of women with Plasmodium vivax mono-infection. S5 Table. The baseline characteristics of patients with Plasmodium falciparum infection, including both P. falciparum mono-infection and co-infection of P. falciparum and Plasmodium vivax. S6 Table. Cumulative proportion of fever and parasite clearance of falciparum and vivax for each treatment arm among pregnant women with history of fever or documented fever at enrolment. S7 Table. Description of gametocyte carriage, congenital and placental malaria. S8 Table. Univariable and multivariable analyses of the risk of PCR-corrected treatment failure in pregnant women with uncomplicated falciparum malaria using a Cox proportional hazard model. S9 Table. Univariable and multivariable analyses on the risk of PCR-corrected treatment failure in pregnant women with uncomplicated falciparum malaria using a Cox proportional hazard model with Pfkelch13 mutations. S10 Table. Prevalence of symptoms before and after treatment. S11 Table. Description of pregnancy outcomes. S12 Table. Details of pregnant women who had miscarriage or stillbirth. S13 Table. Details of congenital abnormality and ICD-10 coding. S14 Table. Details of neonatal mortality. S15 Table. Univariable and multivariable linear regression analyses of the characteristics associated with gestational week at birth among those who had malaria in pregnancy. S16 Table. Univariable and multivariable linear regression analyses of the characteristics associated with SGA z-score (birthweight for gestational age and newborn sex at birth). S17 Table. Birth outcomes in pregnant women who had malaria and were enrolled in the first trimester. S1 Figure. Monthly number of pregnant women with malaria for each malaria species over the study period (from February 2010 to August 2016). S2 Figure. Kaplan-Meier survival curves for antimalarials in pregnancy: Panel a. recurrence of any malaria species, Panel b. Plasmodium falciparum PCR-corrected efficacy censoring intercalated Plasmodium vivax malaria, Panel c. P. falciparum PCR-uncorrected efficacy , and Panel d. P. vivax parasitaemia after P. falciparum mono-infection. S3 Figure. Kaplan-Meier survival curves for parasite clearance of Plasmodium falciparum (Panel a) or Plasmodium vivax (Panel b) for each treatment arm. S4 Figure. Fractional change in haematocrit from baseline during the follow-up for each species (Panel a) or treatment stratified by malaria species (Panel b).

19. MOESM4 of The epidemiology of subclinical malaria infections in South-East Asia: findings from cross-sectional surveys in Thailandâ Myanmar border areas, Cambodia, and Vietnam

Author

Imwong, Mallika, Nguyen, Thuy, Rupam Tripura, Peto, Tom, Lee, Sue, Khin Lwin, Preyanan Suangkanarat, Atthanee Jeeyapant, Benchawan Vihokhern, Klanarong Wongsaen, Hue, Dao, Dong, Le, Tam-Uyen Nguyen, Lubell, Yoel, Seidlein, Lorenz, Mehul Dhorda, Cholrawee Promnarate, Snounou, Georges, Benoit Malleret, RĂŠnia, Laurent, Keereecharoen, Lilly, Singhasivanon, Pratap, Pasathorn Sirithiranont, Jem Chalk, Chea Nguon, Hien, Tran, Day, Nicholas, White, Nicholas, Dondorp, Arjen, and Francois Nosten

Subjects
3. Good health
Abstract

Additional file 4. The results of RDT, light microscopy, and HVUSqPCR in Cambodia, Thailand Myanmar border areas, and Vietnam (disaggregated by village).

20. MOESM2 of The epidemiology of subclinical malaria infections in South-East Asia: findings from cross-sectional surveys in Thailandâ Myanmar border areas, Cambodia, and Vietnam

Author

Imwong, Mallika, Nguyen, Thuy, Rupam Tripura, Peto, Tom, Lee, Sue, Khin Lwin, Preyanan Suangkanarat, Atthanee Jeeyapant, Benchawan Vihokhern, Klanarong Wongsaen, Hue, Dao, Dong, Le, Tam-Uyen Nguyen, Lubell, Yoel, Seidlein, Lorenz, Mehul Dhorda, Cholrawee Promnarate, Snounou, Georges, Benoit Malleret, RĂŠnia, Laurent, Keereecharoen, Lilly, Singhasivanon, Pratap, Pasathorn Sirithiranont, Jem Chalk, Chea Nguon, Hien, Tran, Day, Nicholas, White, Nicholas, Dondorp, Arjen, and Francois Nosten

Subjects
parasitic diseases, 3. Good health
Abstract

Additional file 2. Reasons why individuals were not included in the malaria surveys.

21. MOESM5 of The epidemiology of subclinical malaria infections in South-East Asia: findings from cross-sectional surveys in Thailandâ Myanmar border areas, Cambodia, and Vietnam

Author

Imwong, Mallika, Nguyen, Thuy, Rupam Tripura, Peto, Tom, Lee, Sue, Khin Lwin, Preyanan Suangkanarat, Atthanee Jeeyapant, Benchawan Vihokhern, Klanarong Wongsaen, Hue, Dao, Dong, Le, Tam-Uyen Nguyen, Lubell, Yoel, Seidlein, Lorenz, Mehul Dhorda, Cholrawee Promnarate, Snounou, Georges, Benoit Malleret, RĂŠnia, Laurent, Keereecharoen, Lilly, Singhasivanon, Pratap, Pasathorn Sirithiranont, Jem Chalk, Chea Nguon, Hien, Tran, Day, Nicholas, White, Nicholas, Dondorp, Arjen, and Francois Nosten

Subjects
parasitic diseases, 3. Good health
Abstract

Additional file 5. Sensitivity, specificity, positive predictive value and negative predictive value of RDTs and microscopy compared with HVUSqPCR species detection (disaggregated by village).

22. MOESM3 of The epidemiology of subclinical malaria infections in South-East Asia: findings from cross-sectional surveys in Thailandâ Myanmar border areas, Cambodia, and Vietnam

Author

Imwong, Mallika, Nguyen, Thuy, Rupam Tripura, Peto, Tom, Lee, Sue, Khin Lwin, Preyanan Suangkanarat, Atthanee Jeeyapant, Benchawan Vihokhern, Klanarong Wongsaen, Hue, Dao, Dong, Le, Tam-Uyen Nguyen, Lubell, Yoel, Seidlein, Lorenz, Mehul Dhorda, Cholrawee Promnarate, Snounou, Georges, Benoit Malleret, RĂŠnia, Laurent, Keereecharoen, Lilly, Singhasivanon, Pratap, Pasathorn Sirithiranont, Jem Chalk, Chea Nguon, Hien, Tran, Day, Nicholas, White, Nicholas, Dondorp, Arjen, and Francois Nosten

Subjects
parasitic diseases, 3. Good health
Abstract

Additional file 3. Study population characteristics in the malaria surveys (disaggregated by village).

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