Background: TB surveillance and preventing the further spread of the disease need the full knowledge of the biological characteristics influencing TB and detecting mathematical patterns to interpret the mechanism of TB spread. These models can provide explanations and knowledge of the dynamics of diseases and can be used for forecasting the ensuing values. To determine the possible number of patients, the time ahead is vital for decision making in public health. However, it is essential to determine forecasts' accuracy utilizing genuine forecasts. Thus, we obtained the TB cases from April 2007 until March 2018 in Razavi Khorasan province to develop a fit model and forecast the number of TB cases for the next 24 months. Methods: We considered a time series of monthly incidence counts of TB in Razavi Khorasan province from April 2007 until March 2018. The data included total TB, pulmonary TB, new pulmonary TB, retreatment TB, and extrapulmonary TB cases. For choosing models and forecasting, we use about 20% of all data (24 data) for testing and the rest for training the model. The optimization of parameters was done automatically according to the smallest root mean squared error for these time-series analysis techniques with STATA. The models were EWMAs models (single exponential and double exponential smoothers) and totally, we compared the quality of forecasts provided by EWMAs models through the stand-alone measurement (RMSE). Results: The patterns of raw series of total TB, pulmonary TB, and new pulmonary TB were almost the same. They illustrated slowly downward trends with oscillation around the trend that was a property of cyclic trend. For retreatment TB and extrapulmonary TB cases, reductions occurred over time although with no pattern. The results of statistical models indicated that the values of smoothing constants of all series were near zero that indicated a very smooth series with slowly changing counts. Total TB, pulmonary TB, and new pulmonary TB series had double exponential patterns with noisy and long-standing trend and they might be increasing in the 24 months ahead. Retreatment TB and extrapulmonary TB series had simple exponential patterns with noisy and without secular trends; they might be with no changes in the 24 months ahead. Conclusions: The end TB strategy, MDG 6, target 8 is to stop and start to inverse the incidence of TB by 2015 and we joined this strategy in January 2006. However, TB control remains one of the main public health concerns. In recent years, our country has experienced immigrants from neighboring countries, sanctions or/and attacks with category C of biological agents in moving toward tuberculosis elimination. Our implementation requires changes in strategies and activities that should evolve over time. The findings of this study are helpful in achieving this goal.
Background: Since the Coronavirus disease 19 (Covid-19) rampaged in Iran, three waves of the epidemic occurred. Objective: In the present study, two issues are considered. First: What proportion of the people adhere to the mitigation approaches towards the disease? Second: Which are the reasons to disobey these rules? Methods: A cross-sectional, population-based phone survey was applied among the population aged over 16 years in Mashhad between November 5 and December 1, 2020. A valid and reliable knowledge, attitude, and performance (KAP (designed questionnaire was used and logistic regression was performed with STATA 14. Results: The final sample size was 776; 90.59, 89.8 and 48.1% of the participants had sufficient reliable knowledge, attitude, and practice, respectively; 20.1% of the participants did not wear masks; nearly half of them visited traditional healers for the prevention and cure; 97.8% of them believed the efficiency of the vaccine and stated that they will consume it if it is distributed. Among the sociodemographic factors, only the unemployed had low adherence to the preventive approach; 51.7% of the main worry was the weak economic situation and 69% of jobs and expenditures were poorly affected. The odds ratio (OR) for optimising attitude reduced from 4.64 to 3.22, and for good performance from 5.64 to 5.43 after adjusting for the economic, knowledge and perception factors. Conclusion: Despite all the health rules and probably COVID-19 vaccines global access (COVAX), it seems that the most effective way to reverse this horrific wave and its economic consequences is the improvement of the economy and livelihood of the society.
Background: The basic reproduction number (R0) is an epidemic threshold parameter that indicates the magnitude of disease transmission and thus allows suggestions for the planning of control measures. Objectives: Our aim in this study was to compare different approaches for estimating R0 in the early stage of the SARS-CoV-2 outbreak and discern the best-fitting model. Methods: The dataset was derived from cumulative laboratory-confirmed COVID-19 cases from 26th February to 30th May 2020 in Iran. The methods of exponential growth (EG) rate, maximum likelihood (ML), time-dependent (TD) reproduction number, attack rate (AR), and sequential Bayesian (SB) model were used. The gamma distribution (mean 4.41 ± 3.17 days) was used for serial interval (SI) distribution. The best-fitting method was selected according to the lowest root mean square error (RMSE). Results: We obtained the following estimated R0 [95% confidence interval]: 1.55 [1.54; 1.55], 1.46 [1.45; 1.46], 1.31 [1.30; 1.32], and 1.40 [1.39; 1.41] using EG, ML, TD, and SB methods, respectively. Additionally, the EG and ML methods showed an overestimation of R0, and the SB method showed to be under-fitting in the estimation of R0. The AR method estimated R0 equal to one. The TD method had the lowest RMSE. Conclusions: The simulated and actual R0 of TD showed that this method had a good fit for actual data and the lowest RMSE. Therefore, the TD method is the most appropriate method with the best performance in estimating actual R0 values.
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