Last data update: May 06, 2024. (Total: 46732 publications since 2009)
Records 1-5 (of 5 Records) |
Query Trace: Morton LC[original query] |
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Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines.
Pollett S , Johansson MA , Reich NG , Brett-Major D , Del Valle SY , Venkatramanan S , Lowe R , Porco T , Berry IM , Deshpande A , Kraemer MUG , Blazes DL , Pan-Ngum W , Vespigiani A , Mate SE , Silal SP , Kandula S , Sippy R , Quandelacy TM , Morgan JJ , Ball J , Morton LC , Althouse BM , Pavlin J , van Panhuis W , Riley S , Biggerstaff M , Viboud C , Brady O , Rivers C . PLoS Med 2021 18 (10) e1003793 BACKGROUND: The importance of infectious disease epidemic forecasting and prediction research is underscored by decades of communicable disease outbreaks, including COVID-19. Unlike other fields of medical research, such as clinical trials and systematic reviews, no reporting guidelines exist for reporting epidemic forecasting and prediction research despite their utility. We therefore developed the EPIFORGE checklist, a guideline for standardized reporting of epidemic forecasting research. METHODS AND FINDINGS: We developed this checklist using a best-practice process for development of reporting guidelines, involving a Delphi process and broad consultation with an international panel of infectious disease modelers and model end users. The objectives of these guidelines are to improve the consistency, reproducibility, comparability, and quality of epidemic forecasting reporting. The guidelines are not designed to advise scientists on how to perform epidemic forecasting and prediction research, but rather to serve as a standard for reporting critical methodological details of such studies. CONCLUSIONS: These guidelines have been submitted to the EQUATOR network, in addition to hosting by other dedicated webpages to facilitate feedback and journal endorsement. |
Identification and evaluation of epidemic prediction and forecasting reporting guidelines: A systematic review and a call for action
Pollett S , Johansson M , Biggerstaff M , Morton LC , Bazaco SL , Brett Major DM , Stewart-Ibarra AM , Pavlin JA , Mate S , Sippy R , Hartman LJ , Reich NG , Maljkovic Berry I , Chretien JP , Althouse BM , Myer D , Viboud C , Rivers C . Epidemics 2020 33 100400 INTRODUCTION: High quality epidemic forecasting and prediction are critical to support response to local, regional and global infectious disease threats. Other fields of biomedical research use consensus reporting guidelines to ensure standardization and quality of research practice among researchers, and to provide a framework for end-users to interpret the validity of study results. The purpose of this study was to determine whether guidelines exist specifically for epidemic forecast and prediction publications. METHODS: We undertook a formal systematic review to identify and evaluate any published infectious disease epidemic forecasting and prediction reporting guidelines. This review leveraged a team of 18 investigators from US Government and academic sectors. RESULTS: A literature database search through May 26, 2019, identified 1467 publications (MEDLINE n = 584, EMBASE n = 883), and a grey-literature review identified a further 407 publications, yielding a total 1777 unique publications. A paired-reviewer system screened in 25 potentially eligible publications, of which two were ultimately deemed eligible. A qualitative review of these two published reporting guidelines indicated that neither were specific for epidemic forecasting and prediction, although they described reporting items which may be relevant to epidemic forecasting and prediction studies. CONCLUSIONS: This systematic review confirms that no specific guidelines have been published to standardize the reporting of epidemic forecasting and prediction studies. These findings underscore the need to develop such reporting guidelines in order to improve the transparency, quality and implementation of epidemic forecasting and prediction research in operational public health. |
Histidine-rich protein 2 (pfhrp2) and pfhrp3 gene deletions in Plasmodium falciparum isolates from select sites in Brazil and Bolivia.
Rachid Viana GM , Akinyi Okoth S , Silva-Flannery L , Lima Barbosa DR , Macedo de Oliveira A , Goldman IF , Morton LC , Huber C , Anez A , Dantas Machado RL , Aranha Camargo LM , Costa Negreiros do Valle S , Marins Povoa M , Udhayakumar V , Barnwell JW . PLoS One 2017 12 (3) e0171150 More than 80% of available malaria rapid diagnostic tests (RDTs) are based on the detection of histidine-rich protein-2 (PfHRP2) for diagnosis of Plasmodium falciparum malaria. Recent studies have shown the genes that code for this protein and its paralog, histidine-rich protein-3 (PfHRP3), are absent in parasites from the Peruvian Amazon Basin. Lack of PfHRP2 protein through deletion of the pfhrp2 gene leads to false-negative RDT results for P. falciparum. We have evaluated the extent of pfhrp2 and pfhrp3 gene deletions in a convenience sample of 198 isolates from six sites in three states across the Brazilian Amazon Basin (Acre, Rondonia and Para) and 25 isolates from two sites in Bolivia collected at different times between 2010 and 2012. Pfhrp2 and pfhrp3 gene and their flanking genes on chromosomes 7 and 13, respectively, were amplified from 198 blood specimens collected in Brazil. In Brazil, the isolates collected in Acre state, located in the western part of the Brazilian Amazon, had the highest percentage of deletions for pfhrp2 25 (31.2%) of 79, while among those collected in Rondonia, the prevalence of pfhrp2 gene deletion was only 3.3% (2 out of 60 patients). In isolates from Para state, all parasites were pfhrp2-positive. In contrast, we detected high proportions of isolates from all 3 states that were pfhrp3-negative ranging from 18.3% (11 out of 60 samples) to 50.9% (30 out of 59 samples). In Bolivia, only one of 25 samples (4%) tested had deleted pfhrp2 gene, while 68% (17 out of 25 samples) were pfhrp3-negative. Among the isolates tested, P. falciparum pfhrp2 gene deletions were present mainly in those from Acre State in the Brazilian Amazon. These results indicate it is important to reconsider the use of PfHRP2-based RDTs in the western region of the Brazilian Amazon and to implement appropriate surveillance systems to monitor pfhrp2 gene deletions in this and other parts of the Amazon region. |
Plasmodium falciparum Drug-Resistant Haplotypes and Population Structure in Postearthquake Haiti, 2010.
Morton LC , Huber C , Okoth SA , Griffing S , Lucchi N , Ljolje D , Boncy J , Oscar R , Townes D , McMorrow M , Chang MA , Udhayakumar V , Barnwell JW . Am J Trop Med Hyg 2016 95 (4) 811-816 Chloroquine (CQ) remains the first-line treatment of malaria in Haiti. Given the challenges of conducting in vivo drug efficacy trials in low-endemic settings like Haiti, molecular surveillance for drug resistance markers is a reasonable approach for detecting resistant parasites. In this study, 349 blood spots were collected from suspected malaria cases in areas in and around Port-au-Prince from March to July 2010. Among them, 121 samples that were Plasmodium falciparum positive by polymerase chain reaction were genotyped for drug-resistant pfcrt, pfdhfr, pfdhps, and pfmdr1 alleles. Among the 108 samples that were successfully sequenced for CQ resistant markers in pfcrt, 107 were wild type (CVMNK), whereas one sample carried a CQ-resistant allele (CVIET). Neutral microsatellite genotyping revealed that the CQ-resistant isolate was distinct from all other samples in this study. Furthermore, the remaining parasite specimens appeared to be genetically distinct from other reported Central and South American populations. |
Clonal population expansion in an outbreak of Plasmodium falciparum on the northwest coast of Ecuador.
Saenz FE , Morton LC , Okoth SA , Valenzuela G , Vera-Arias CA , Velez-Alvarez E , Lucchi NW , Castro LE , Udhayakumar V . Malar J 2014 13 Suppl 1 497 BACKGROUND: Determining the source of malaria outbreaks in Ecuador and identifying remaining transmission foci will help in malaria elimination efforts. In this study, the genetic signatures of Plasmodium falciparum isolates, obtained from an outbreak that occurred in northwest Ecuador from 2012 to 2013, were characterized. METHODS: Molecular investigation of the outbreak was performed using neutral microsatellites, drug resistance markers and pfhrp2 and pfhrp3 genotyping. RESULTS: A majority of parasite isolates (31/32) from this outbreak were of a single clonal type that matched a clonal lineage previously described on the northern coast of Peru and a historical isolate from Ecuador. All but one isolate carried a chloroquine-resistant pfcrt genotype and sulfadoxine- and pyrimethamine-sensitive pfdhps and pfdhfr genotypes. Pfmdr1 mutations were identified in codons 184 and 1042. In addition, most samples (97 %) showed presence of pfhrp2 gene. CONCLUSIONS: This study indicates that parasites from a single clonal lineage largely contributed to this outbreak and this lineage was found to be genetically related to a lineage previously reported in the Peruvian coast and historical Ecuadorian parasites. |
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