Mathematical Sciences: Population Dynamics of Infectious    Diseases
{'Code': '03040100', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}
{'SignBlockName': 'Michael Steuerwalt', 'PO_EMAI': None, 'PO_PHON': None}
This project will study ways in which heterogeneities                      associated with age structure, social habits, or genetic                        variability within the host population can interact with the                    nonlinearities inherent in the transmission of infectious                       diseases to produce outcomes that are not easily intuited.                           The first part of the project focuses on various aspects of                specific viral and bacterial infections in the USA and UK;                      measles, rubella, mumps, polio, pertussis and HIV.  Models that                 account for observed age-specific differences in infection                      probabilities will be studied tested against epidemiological data               and applied to compare different immunization strategies.                       Equations describing the epidemic spread of HIV infection among                 populations of homosexual males will be developed, taking account               of the AIDS wide distribution reported in degrees of sexual                     activity; potential applications of the estimation of                           epidemiological parameters and projected effects of changes in                  sexual habits will be explored.                                                      Second, mathematical models for the transmission dynamics of               helminth infections (specially Ascaris and various filarial                     infections) will be studied with attention to comparing the                     effects of different control strategies.                                             At a more abstract level, the cyclic and chaotic properties                of models for arthropod populations regulated by lethal pathogens               will be investigated, partly with the aim of understanding                      relations between life history parameters and dynamical behavior.               Building on earlier work, these studies will be extended to                     combine population genetics with population biology in pursuit of               a better understanding of the coevolution of host-parasite                      associations.                                                                        Mathematical models in epidemiology are often based on the                 qualitative theory of differential equations and constitute a                   prime example of applied mathematics in life sciences.  Dr. May                 is the most prominent representative of this research direction                 in the U.S.
{'FirstName': 'Robert', 'LastName': 'May', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert M May', 'EmailAddress': None, 'NSF_ID': '000103518', 'StartDate': '07/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Princeton University', 'CityName': 'PRINCETON', 'ZipCode': '085442001', 'PhoneNumber': '6092583090', 'StreetAddress': '1 NASSAU HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'NJ1YPQXQG7U5', 'ORG_LGL_BUS_NAME': 'THE TRUSTEES OF PRINCETON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
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{'Code': '1266', 'Text': 'APPLIED MATHEMATICS'}
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8703503.xml'}