You're probably going to need to give a few more details on this one.  What are the units?  In the medical literature a survival rate is usually the percent (or proportion) of individuals that survive to a given time.  So you might say that the 5 yr survival rate for treated breast cancer is 79% (or 0.79).  Since neither 1% nor 100% make any sense in the context I'm guessing this is not what you're referring to.  In ecology, if you assume a constant rate of density-independent mortality you can model proportional survival as p = ert where r is the mortality rate and t is the time.  In this case r would have units of t-1 (inverse time).

if the survival rate is 1 per day (let's call this r) and is assumed to be constant throughout the entire lifespan, then the average life expectancy is 1/r so 1 day and the standard deviation is 1/r so also 1 day (see exponential distribution in G. Cowan - statistical data analysis - 1998). If you want to calculate what is the proportion of individuals in a cohort that survives until a certain point (and vice versa), then look at Cox and Oakes - analysis of survival data - 1984: the survivor function is exp(-rt) so 5% of the cohort will still be alive after approx. 3 days when r = 1 day^-1.

is it clear ?

Thanks  for your responses, the daily survival rate was calculated from  the parous rate  of 100% taking the gonotrophic cycle to be 2.5 days.  What is the life expectancy? 

Ok, got it.  S=pg where S is the parous rate, p the proportional daily survival and g is the gonotrophic cycle (Davison, 1959, Nature, 174, 792-793).  However, this is only true given a certain number of assumptions, one of which is that the population size is stable.  If the 100% parous rate is correct, then the population is not stable.  Given a 'g' of 2.5, it takes 2.5 d for a newly hatched female to become parous.  Thus, if 100% of the population is parous then there must be no newly hatched females so the population can't be stable and thus does not meet the assumptions of the model and that equation can't be used to calculate the survival rate.  Stefan is right; if the daily survival rate is 100%, then they never die. . .

Two possibilities occur to the mind.  1 is that your data is wrong (i.e. the parous rate is less that 100%), or that it's late enough in the season that new mosquitos aren't hatching and all the already hatched females have laid eggs already.

    Thanks to all your contributions , It was  on my  data analysis based on the  indoor/outdoor and night  hourly distribution of the parous mosquitoes that  I recorded 100% parity in some anopheline species  particular the endophilic ones