Materials Map

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2022Significance of nested PCR testing for the detection of low-density malaria infection amongst febrile patients from the Malaria Elimination Demonstration Project in Mandla, Madhya Pradesh, India8citations
  • 2021Assessment of ASHA for knowledge, diagnosis and treatment on malaria in Mandla district of Madhya Pradesh as part of the malaria elimination demonstration project17citations

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Chart of shared publication
Das, Aparup
2 / 2 shared
Kaur, Harpreet
2 / 6 shared
Mishra, Ashok K.
2 / 2 shared
Jayswar, Himanshu
2 / 2 shared
Telasey, Vinay
1 / 1 shared
Singh, Mrigendra P.
1 / 2 shared
Singh, Akansha
1 / 2 shared
Rajvanshi, Harsh
1 / 1 shared
Bhandari, Sneha
1 / 1 shared
Nisar, Sekh
2 / 2 shared
Rajvanshi, Dr. Harsh
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Sharma, Ravendra K.
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Saha, Kalyan B.
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Shukla, Man Mohan
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Wattal, Suman L.
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Verma, Arvind
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Saxena, Nishant
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2022
2021

Co-Authors (by relevance)

  • Das, Aparup
  • Kaur, Harpreet
  • Mishra, Ashok K.
  • Jayswar, Himanshu
  • Telasey, Vinay
  • Singh, Mrigendra P.
  • Singh, Akansha
  • Rajvanshi, Harsh
  • Bhandari, Sneha
  • Nisar, Sekh
  • Rajvanshi, Dr. Harsh
  • Sharma, Ravendra K.
  • Saha, Kalyan B.
  • Shukla, Man Mohan
  • Wattal, Suman L.
  • Verma, Arvind
  • Saxena, Nishant
OrganizationsLocationPeople

article

Significance of nested PCR testing for the detection of low-density malaria infection amongst febrile patients from the Malaria Elimination Demonstration Project in Mandla, Madhya Pradesh, India

  • Das, Aparup
  • Kaur, Harpreet
  • Mishra, Ashok K.
  • Jayswar, Himanshu
  • Telasey, Vinay
  • Singh, Mrigendra P.
  • Singh, Akansha
  • Rajvanshi, Harsh
  • Bhandari, Sneha
  • Nisar, Sekh
  • Lal, Altaf A.
Abstract

<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Low-density malaria infections (LDMI) are defined as infections that are missed by the rapid diagnostic test (RDT) and/or microscopy which can lead to continued transmission and poses a challenge in malaria elimination efforts. This study was conducted to investigate the prevalence of LDMI in febrile cases using species-specific nested Polymerase Chain Reaction (PCR) tests in the Malaria Elimination Demonstration Project, where routine diagnosis was conducted using RDT.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>Every 10th fever case from a cross-sectional community based fever surveillance was tested with RDT, microscopy and nested PCR. Parasite DNA was isolated from the filter paper using Chelex based method. Molecular diagnosis by nested PCR was performed targeting 18SrRNA gene for <jats:italic>Plasmodium</jats:italic> species.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>The prevalence of malaria was 2.50% (436/17405) diagnosed by PCR, 1.13% (196/17405) by RDT, and 0.68% (118/ 17,405) by microscopy. Amongst 17,405 febrile samples, the prevalence of LDMI was 1.51% (263/17405) (95% CI 1.33–1.70), which were missed by conventional methods. Logistic regression analysis revealed that illness during summer season [OR = 1.90 (p &lt; 0.05)] and cases screened within three days of febrile illness [OR = 5.27 (p &lt; 0.001)] were the statistically significant predictors of LDMI.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>The prevalence of malaria among febrile cases using PCR was 2.50% (436/17405) as compared to 1.13% (196/17405) by RDT. Higher number of the LDMI cases were found in subjects with ≤ 3 days mean duration of reported fever, which was statistically significant (p &lt; 0.001). This observation suggests that an early detection of malaria with a more sensitive diagnostic method or repeat testing of the all negative cases may be useful for curtailing malaria transmission. Therefore, malaria elimination programme would benefit from using more sensitive and specific diagnostic methods, such as PCR.</jats:p></jats:sec>

Topics
  • density
  • size-exclusion chromatography
  • chemical ionisation
  • microscopy