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In summary, we found that epidemic profiles differ in local areas of the United States.
The epidemic profiles of dengue fever are different from one year to another in Taiwan.
Three epidemic profiles can arise depending on the degree of population mixing.
We find that both models, despite the difference in the data integration and model structure, provide epidemic profiles with spatio-temporal patterns in very good agreement.
These three epidemic profiles arise from the interplay between the immunological and epidemiological dynamics that modulates the effective reproduction number R e (t) throughout the epidemic.
Our simulations indicate that small changes in the initial number of infections may result in different epidemic profiles exhibiting more than one infection wave.
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Regardless of epidemic profile, investments in all countries should be submitted to this test: What public health impact can they be expected to achieve?
This will require resource allocation that reflects the epidemic profile of a country, and adequate investment in the needs of most-at-risk populations even where epidemiological studies have ignored their existence.
This epidemic profile observed in São Paulo was also detected earlier in Rio de Janeiro and Rio Grande do Sul [ 5, 13– 15, 32– 32].
Although reporting bias probably affects these data, the reported pattern is consistent with the national epidemic profile for 2009 2010.
The flusurvey-adjusted epidemic profile is more consistent with the pattern of H1N1v deaths, 80% of which occurred during the autumn wave.
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