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We assume that a process is properly described by a two-parameter extension of the zero-inflated Poisson distribution, which can be used for modeling count data with an excessive number of zero and non-zero values. Two different upper-sided cumulative sum-type schemes are considered, both suitable for the detection of increasing shifts in the average of the process. Aspects of their statistical design are discussed and their performance is compared under various out-of-control situations. Changes in both parameters of the process are considered. Finally, the monitoring of the monthly cases of poliomyelitis in the USA is given as an illustrative example.<\/jats:p>","DOI":"10.1177\/0962280216641985","type":"journal-article","created":{"date-parts":[[2016,4,14]],"date-time":"2016-04-14T21:03:43Z","timestamp":1460667823000},"page":"622-641","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":13,"title":["Cumulative sum control charts for monitoring geometrically inflated Poisson processes: An application to infectious disease counts data"],"prefix":"10.1177","volume":"27","author":[{"given":"Athanasios C","family":"Rakitzis","sequence":"first","affiliation":[{"name":"LUNAM Universit\u00e9, Universit\u00e9 de Nantes & IRCCyN UMR CNRS, Nantes, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philippe","family":"Castagliola","sequence":"additional","affiliation":[{"name":"LUNAM Universit\u00e9, Universit\u00e9 de Nantes & IRCCyN UMR CNRS, 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