A case of a male infant at the age of 3 months with cytomegalovirus (CMV) infection, diagnosed 40 days after the first symptoms, was discussed. While the right dosage and schedule during the initial treatment with ganciclovir (Cymevene) were agreed on, the right time of further application of anti-CMV IgG (Cytotest) and ganciclovir was unclear. Daily mean temperature was taken as an overall measure based on 7 single readings (6:00, 9:00, 12:00, 15:00, 18:00, 21:00 and 24:00 h +/- 10 min). Dynamics of daily mean temperature was studied by descriptive statistics, regression analysis, autocorrelation and periodogram regression analysis (software package "6-D Statistics" PC ver.4.5-98 by B. P. Komitov) with the purpose of identifying the time periods of viral DNA replications and CMV population growth inclinations. A five-step procedure was applied: (1) description of a tendency in the daily mean temperature; (2) studying variations in time series of the daily mean temperature; (3) decomposition of cyclic variations; (4) reconstruction of time series; (5) best model determination and forecasting. Three main cycles in variations of daily mean temperature were revealed (period T approximately 2.25-3.25, 5.5 and 12.25 days, p < 0.05) until the 37th day of therapy, when a strongly decreasing trend of daily mean temperature emerged. The cycle of 2.25-3.25 days disappeared and the daily mean temperature continued to decrease significantly on the background of improvement of the clinical status. It was concluded that (1) cyclic patterns in daily mean temperature (periods T = 2.25-3.25 and 12.25 days) during the etiologic medication stages could be due to the life-cycle of 2-4 days of the cytomegalovirus and a cycle in the viral population growth, respectively. The above findings confirmed previous results on the period of viral DNA replication from in vitro studies. It was possible to forecast the right moment of replication and viral load to adjust the treatment schemes and improve the outcome; (2) the complex time-series approach has shown to be very useful and effective in analyzing and forecasting the temporal dynamics of daily mean temperature in order to optimize the clinical management in this particular case of an infant with CMV infection.