Understanding Society User Support

Hi there,
I am trying to create a variable based on longcovid that matches the number of observations in hadsymp excluding individuals residing in Wales who responded in Welsh.
My understanding is that everyone who reported having symptoms of covid would have answered the longcovid question. However, based on the dictionary, the question is asked "...if previously reported having covid symptoms, and not reported having symptoms in current survey". Are individuals asked this question only once if they reported symptoms in the last survey or are they followed up in every survey? My goal is to create a new variable for longcovid where 0 covers individuals who never reported having covid symptoms and 1 if they report long-term symptoms. I attempted a version below (not excluding Welsh responses yet but I doubt this would account for a substantial number of observations) and would appreciate advice on how to properly do this.

gen covid = .
replace covid = 1 if hadsymp 1
replace covid = 0 if hadsymp 2

tab covid

covid |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |    115,704       94.03       94.03
          1 |      7,343        5.97      100.00
------------+-----------------------------------
      Total |    123,047      100.00

egen anycovid = max(covid 1), by(pidp)
replace anycovid = . if covid .

tab anycovid

anycovid |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |     89,451       72.70       72.70
          1 |     33,596       27.30      100.00
------------+-----------------------------------
      Total |    123,047      100.00

*1 is the number of observations that takes the value 1 at least once i.e, the individual reports covid in at least
*one wave

gen longcovid_main = .
replace longcovid_main = 1 if longcovid 1
replace longcovid_main = 0 if longcovid 2
replace longcovid_main = 0 if anycovid == 0

tab longcovid_main

longcovid_m |
ain | Freq. Percent Cum.
------------+-----------------------------------
0 | 90,113 92.34 92.34
1 | 7,474 7.66 100.00
------------+-----------------------------------
Total | 97,587 100.00

Many thanks
Karen