I am working with weekly data and I am running into troubles when analyzing them because of their inconsistent nature. By inconsistent nature, I mean that not every month is made of the same number of weeks so that some weeks span over two subsequent months and the same holds for months over subsequent years.

Just to give you an example let's suppose I have a week beginning on March 28 ending on April 3. And let's suppose I have just a figure for the whole week, while I should have two figures, one for each month.

Since I need to impute each figure to a specific year, month and week, how should I proceed in order not to generate any misinterpretation?

I am working with weekly data and I am running into troubles when analyzing them because of their inconsistent nature. By inconsistent nature, I mean that not every month is made of the same number of weeks so that some weeks span over two subsequent months and the same holds for months over subsequent years.

Just to give you an example let's suppose I have a week beginning on March 28 ending on April 3. And let's suppose I have just a figure for the whole week, while I should have two figures, one for each month.

The purpose of this dataset is to run some descriptive analysis, thus I need to be able to analyze data by weeks, (aggregated) by months and (aggregated) by years. And I would like to aggregate them properly, e.g. deaths across two months should be (as much as possible) imputed to each month correctly.

How would you proceed? Any technique better than the others?