{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T07:35:52Z","timestamp":1774078552046,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,6,16]],"date-time":"2021-06-16T00:00:00Z","timestamp":1623801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1513657"],"award-info":[{"award-number":["1513657"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Infectious Disease Reports"],"abstract":"<jats:p>Coccidioidomycosis is an infectious disease of humans and other mammals that has seen a recent increase in occurrence in the southwestern United States, particularly in California. A rise in cases and risk to public health can serve as the impetus to apply newly developed methods that can quickly and accurately predict future caseloads. The recursive and Hawkes point process models with various triggering functions were fit to the data and their goodness of fit evaluated and compared. Although the point process models were largely similar in their fit to the data, the recursive point process model offered a slightly superior fit. We explored forecasting the spread of coccidioidomycosis in California from December 2002 to December 2017 using this recursive model, and we separated the training and testing portions of the data and achieved a root mean squared error of just 3.62 cases\/week.<\/jats:p>","DOI":"10.3390\/idr13020052","type":"journal-article","created":{"date-parts":[[2021,6,16]],"date-time":"2021-06-16T21:58:32Z","timestamp":1623880712000},"page":"558-570","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Point Process Models for the Spread of Coccidioidomycosis in California"],"prefix":"10.3390","volume":"13","author":[{"given":"Jiajia","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Statistics, University of California, Los Angeles, CA 92521, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ryan J.","family":"Harrigan","sequence":"additional","affiliation":[{"name":"Center for Tropical Research, Institute of the Environment and Sustainability, University of California, Los Angeles, CA 92521, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Frederic P.","family":"Schoenberg","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of California, Los Angeles, CA 92521, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,16]]},"reference":[{"key":"ref_1","unstructured":"(2019, March 02). San Luis Obispo County Public Health Department Epidemiologic Profile of Coccidiodomycosis in San Luis Obispo County, CA, Available online: https:\/\/www.slocounty.ca.gov\/getattachment\/4f135e93-609a-4a29-b2c6-d6b80250d072\/Valley-Fever-Profile-Report.aspx."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"308","DOI":"10.3201\/eid2302.160505","article-title":"Risk factors for disseminated Coccidioidomycosis, United States","volume":"23","author":"Odio","year":"2017","journal-title":"Emerg. Infect. Dis."},{"key":"ref_3","unstructured":"Pierce, H. (2019, March 02). Forecasting an Epidemic: How Weather Contributes to Valley Fever Outbreaks. Available online: https:\/\/voiceofoc.org\/2016\/11\/forecasting-an-epidemic-how-weather-contributes-to-valley-fever-outbreaks\/."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Wilson, L., Ting, J., Lin, H., Shah, R., MacLean, M., Peterson, M.W., Stockamp, N., Libke, R., and Brown, P. (2019). The rise of valley fever: Prevalence and cost burden of coccidioidomycosis infection in california. Int. J. Environ. Res. Public Health, 16.","DOI":"10.3390\/ijerph16071113"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1093\/biomet\/58.1.83","article-title":"Spectra of some self-exciting and mutually exciting point processes","volume":"51","author":"Hawkes","year":"1971","journal-title":"Biometrika"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1080\/01621459.1988.10478560","article-title":"Statistical models for earthquake occurrences and residual analysis for point processes","volume":"83","author":"Ogata","year":"1988","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1023\/A:1003403601725","article-title":"Space-time point-process models for earthquake occurrences","volume":"50","author":"Ogata","year":"1998","journal-title":"Ann. Inst. Stat. Math."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1198\/jasa.2011.ap09546","article-title":"Self-exciting point process modeling of crime","volume":"106","author":"Mohler","year":"2011","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1080\/01621459.2011.641402","article-title":"Application of branching point process models to the study of invasive red banana plants in Costa Rica","volume":"107","author":"Balderama","year":"2012","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1550005","DOI":"10.1142\/S2382626615500057","article-title":"Hawkes processes in finance","volume":"1","author":"Bacry","year":"2015","journal-title":"Mark. Microstruct. Liq."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Bauwens, L., and Hautsch, N. (2009). Modelling financial high frequency data using point processes. Handbook of Financial Time Series, Springer.","DOI":"10.1007\/978-3-540-71297-8_41"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1007\/BF00161089","article-title":"Point process models of single-neuron discharges","volume":"3","author":"Johnson","year":"1996","journal-title":"J. Comput. Neurosci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1214\/11-AOAS513","article-title":"Self-exciting hurdle models for terrorist activity","volume":"6","author":"Porter","year":"2012","journal-title":"Ann. Appl. Stat."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1111\/j.1541-0420.2011.01684.x","article-title":"A space-time conditional intensity model for invasive Meningococcal disease occurrence","volume":"68","author":"Meyer","year":"2012","journal-title":"Biometrics"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1271","DOI":"10.1007\/s10463-018-0690-9","article-title":"A recursive point process model for infectious diseases","volume":"51","author":"Schoenberg","year":"2019","journal-title":"Ann. Inst. Stat. Math."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Park, J., Chaffee, A.W., Harrigan, R.J., and Schoenberg, F.P. (2020). A Non-Parametric Hawkes Model of the Spread of Ebola in West Africa. J. Appl. Stat.","DOI":"10.1080\/02664763.2020.1825646"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Althaus, C.L. (2014). Estimating the reproduction number of Ebola Virus (EBOV) during the 2014 outbreak in West Africa. PLoS Curr.","DOI":"10.1371\/currents.outbreaks.91afb5e0f279e7f29e7056095255b288"},{"key":"ref_18","unstructured":"Panhuis, W.V., Cross, A., and Burke, D.S. (2018). Counts of Coccidioidomycosis reported in United States of America: 2002\u20132017 (version 2.0, 1 April 2018): Project Tycho data release. Project Tycho."},{"key":"ref_19","unstructured":"Centers for Disease Control (CDC) (2019, February 26). Valley Fever (Coccidioidomycosis) Statistics, Available online: https:\/\/www.cdc.gov\/fungal\/diseases\/coccidioidomycosis\/statistics.html."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1007\/BF02480216","article-title":"The asymptotic behaviour of maximum likelihood estimators for stationary point processes","volume":"30","author":"Ogata","year":"1978","journal-title":"Ann. Inst. Stat. Math."},{"key":"ref_21","first-page":"299","article-title":"A review of spatio-temporal point processes and their applications","volume":"33","author":"Reinhart","year":"2018","journal-title":"Stat. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Brillinger, D.R., Guttorp, P.M., and Schoenberg, F.P. (2013). Point processes, temporal. Encycl. Environ.","DOI":"10.1002\/9781118445112.stat07484"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1785\/0120120146","article-title":"Facilitated estimation of ETAS","volume":"103","author":"Schoenberg","year":"2013","journal-title":"Bull. Seismol. Soc. Am."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1007\/0-387-31144-0_15","article-title":"Diagnostic analysis of space-time branching processes for earthquakes","volume":"185","author":"Zhuang","year":"2006","journal-title":"Case Stud. Spat. Point Process Model."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1093\/gji\/ggu442","article-title":"Log-likelihood of earthquake models: Evaluation of models and forecasts","volume":"201","author":"Harte","year":"2015","journal-title":"Geophys. J. Int."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1002\/mana.19911510108","article-title":"Second-order characteristics for stochastic structures connected with gibbs point processes","volume":"151","author":"Stoyan","year":"1991","journal-title":"Math. Nachr."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1002\/env.2168","article-title":"Evaluation of space-time point process models using superthinning","volume":"23","author":"Clements","year":"2012","journal-title":"Environmetrics"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1109\/TAC.1974.1100705","article-title":"A new look at the statistical model identification","volume":"19","author":"Akaike","year":"1974","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1128\/CMR.00005-13","article-title":"Recent advances in our understanding of the environmental, epidemiological, immunological, and clinical dimensions of Coccidioidomycosis","volume":"26","author":"Nguyen","year":"2013","journal-title":"Clin. Microbiol. Rev."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1002\/2017GH000095","article-title":"Coccidioidomycosis dynamics in relation to climate in the southwestern united states","volume":"2","author":"Gorris","year":"2018","journal-title":"GeoHealth"}],"container-title":["Infectious Disease Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2036-7449\/13\/2\/52\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:16:41Z","timestamp":1760163401000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2036-7449\/13\/2\/52"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,16]]},"references-count":30,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2021,6]]}},"alternative-id":["idr13020052"],"URL":"https:\/\/doi.org\/10.3390\/idr13020052","relation":{},"ISSN":["2036-7449"],"issn-type":[{"value":"2036-7449","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,6,16]]}}}