This set includes data used in a latent class model to compare testing platforms for detection of antibodies against the Chlamydia trachomatis antigen Pgp3. The analysis was published as: Latent class modeling to compare testing platforms for detection of antibodies against the Chlamydia trachomatis antigen Pgp3. Wiegand RE, Cooley G, Goodhew B, Banniettis N, Kohlhoff S, Gwyn S, Martin DL. Sci Rep. 2018 Mar 9;8(1):4232. doi: 10.1038/s41598-018-22708-9. PMID: 29523810

This dataset contains deidentified data from the National Malaria Surveillance System on the number of malaria cases reported in the United States in 2017, by county. Only counties reporting five or more cases are included in this dataset.

This dataset contains deidentified data from the National Malaria Surveillance System on the number of malaria cases reported in the United States in 2016, by county. Only counties reporting five or more cases are included in this dataset.

This dataset includes deidentified data on patients receiving artesunate through the National Artesunate for Severe Malaria Program from April- December 2019.

This dataset contains the data from the case report form only.
Please see the links below for the other datasets and see the attached document 'Guide to NSAMP Datasets':
Data on Artesunate Dosing- https://data.cdc.gov/dataset/National-Artesunate-for-Severe-Malaria-Program-Art/qan4-gt4k
Data on Follow-On Antimalarial Dosing- https://data.cdc.gov/Global-Health/National-Artesunate-for-Severe-Malaria-Program-Fol/g3k9-gyw7
Data on Microscopy (Parasitemia values)- https://data.cdc.gov/Global-Health/National-Artesunate-for-Severe-Malaria-Program-Mic/v2k9-ctv4

All data can be easily linked using the ParticipantID field, a unique ID number assigned to each participant.

This dataset includes deidentified data on patients receiving artesunate through the National Artesunate for Severe Malaria Program from April- December 2019.

This dataset contains microscopy data only.
Please see the links below for the other datasets and the attached document 'Guide to NASMP Datasets:
Data from Case Report Form- https://data.cdc.gov/Global-Health/National-Artesunate-for-Severe-Malaria-Program-Cas/igaz-icki
Data on Artesunate Dosing- https://data.cdc.gov/dataset/National-Artesunate-for-Severe-Malaria-Program-Art/qan4-gt4k
Data on Follow-On Dosing- https://data.cdc.gov/Global-Health/National-Artesunate-for-Severe-Malaria-Program-Fol/g3k9-gyw7

All data can be easily linked using the ParticipantID field, a unique ID number assigned to each participant.

This dataset includes deidentified data on patients receiving artesunate through the National Artesunate for Severe Malaria Program from April- December 2019.

This dataset contains artesunate dosing data only.
Please see the links below for the other datasets and the attached word document, 'Guide to NASMP Datasets':

Data from Case Report- https://data.cdc.gov/Global-Health/National-Artesunate-for-Severe-Malaria-Program-Cas/igaz-icki

Data on Follow-On Antimalarial Dosing- https://data.cdc.gov/Global-Health/National-Artesunate-for-Severe-Malaria-Program-Fol/g3k9-gyw7

Data on Microscopy (Parasitemia values)- https://data.cdc.gov/Global-Health/National-Artesunate-for-Severe-Malaria-Program-Mic/v2k9-ctv4

All data can be easily linked using the ParticipantID field, a unique ID number assigned to each participant.

This dataset includes deidentified data on patients receiving artesunate through the National Artesunate for Severe Malaria Program from April- December 2019.

This dataset contains the data from the case report form only.
Please see the links below for the other datasets and the attached document 'Guide to NASMP Datasets':
Data from Case Report Form- https://data.cdc.gov/Global-Health/National-Artesunate-for-Severe-Malaria-Program-Cas/igaz-icki
Data on Artesunate Dosing- https://data.cdc.gov/dataset/National-Artesunate-for-Severe-Malaria-Program-Art/qan4-gt4k
Data on Microscopy (Parasitemia values)- https://data.cdc.gov/Global-Health/National-Artesunate-for-Severe-Malaria-Program-Mic/v2k9-ctv4

All data can be easily linked using the ParticipantID field, a unique ID number assigned to each participant.