INTRODUCTION: The study focuses on finding a methodology for evaluating the effectiveness of the nonpharmaceutical intervention in the face of a new pathogen entering the population. Different interventions can have different effectiveness levels in different populations; thus, studying possible correlations and effectiveness among different groups is essential. With better knowledge of the topic, the outbreak management could be done more cost-effectively, reducing the need for antibiotics, vaccines, and possible reduction of infectious diseases caused burden in developing regions. Furthermore, the study aims to determine the ways of using excess mortality as an evaluation technique for nonpharmaceutical interventions used in the Covid-19 pandemic. 

METHOD: The variables in time-series format were used to calculate a cross-correlation score alongside other correlation coefficient tests. With the cross-correlation, the lag will be established to estimate how the variables correlate in the timeline. In addition, the study will attempt to establish the connections between different nonpharmaceutical interventions and their strengths and different age groups.

RESULTS: The most frequent lag scores identified were 1 with 16 observations and 2 with 9 observations. The highest lag score was 4, which was observed once for the dataset of Hungary. The correlation between excess mortality and different harshness of NPI's was calculated. The correlation coefficient ranges from -0.3 to -0.39, indicating an overall low to medium correlation. The highest correlation was detected with stay-at-home requirements (-0.36), workplace closing (-0.37), and gathering restrictions (-0.39). In the final step, age-based correlations were established. The correlation ranged from 0.26 – 0.36, indicating an overall medium correlation. The lowest correlation can be seen in the youngest age group, 15-64 (correlation coefficient of 0.26), while the highest correlation of 0.36 can be seen in the 75-84 age group. Surprisingly the age group 85+ had a little lower correlation than the 75-84 age group.

DISCUSSION AND CONCLUSIONS: A stronger correlation between excess mortality and stringency index was detected in the countries with a higher death per capita. The two groups of intervention effectiveness were established: more effective (school closing, workplace closing, public event limitation, gathering restriction, and stay at home requirement) and less effective (public transport limitation, restriction on internal movement, international travel control, public information campaigns, protection of elderly campaigns). This suggests that NPI effectiveness depends on population size. In the age-group-based analysis, the correlation became stronger with the age increase, indicating nonpharmaceutical intervention effectiveness against high mortality in older adults.