Optimize QuerySets in a Loop with indexes and better SQL

I have a View that returns some statistics about email lists growth. The models involved are:

models.py

class Contact(models.Model):
    email_list = models.ForeignKey(EmailList, related_name='contacts')
    customer = models.ForeignKey('Customer', related_name='contacts')
    status = models.CharField(max_length=8)
    create_date = models.DateTimeField(auto_now_add=True)


class EmailList(models.Model):
    customers = models.ManyToManyField('Customer',
        related_name='lists',
        through='Contact')


class Customer(models.Model):
    is_unsubscribed = models.BooleanField(default=False, db_index=True)
    unsubscribe_date = models.DateTimeField(null=True, blank=True, db_index=True)

In the View what I'm doing is iterating over all EmailLists objects and getting some metrics: the following way:

view.py

class ListHealthView(View):
    def get(self, request, *args, **kwargs):
        start_date, end_date = get_dates_from_querystring(request)

        data = []
        for email_list in EmailList.objects.all():
            # historic data up to start_date
            past_contacts = email_list.contacts.filter(
                status='active',
                create_date__lt=start_date).count()
            past_unsubscribes = email_list.customers.filter(
                is_unsubscribed=True,
                unsubscribe_date__lt=start_date,
                contacts__status='active').count()
            past_deleted = email_list.contacts.filter(
                status='deleted',
                modify_date__lt=start_date).count()
            # data for the given timeframe
            new_contacts = email_list.contacts.filter(
                status='active',
                create_date__range=(start_date, end_date)).count()
            new_unsubscribes = email_list.customers.filter(
                is_unsubscribed=True,
                unsubscribe_date__range=(start_date, end_date),
                contacts__status='active').count()
            new_deleted = email_list.contacts.filter(
                status='deleted',
                modify_date__range=(start_date, end_date)).count()

            data.append({
                'new_contacts': new_contacts,
                'new_unsubscribes': new_unsubscribes,
                'new_deleted': new_deleted,
                'past_contacts': past_contacts,
                'past_unsubscribes': past_unsubscribes,
                'past_deleted': past_deleted,
            })
        return Response({'data': data})

Now this works fine, but as My DB started growing, the response time from this view is above 1s and occasionally will cause long running queries in the Database. I think the most obvious improvement would be to index EmailList.customers but I think maybe it needs to be a compound index ? Also, is there a better way of doing this ? Maybe using aggregates ?

EDIT

After @bdoubleu answer I tried the following:

data = (
    EmailList.objects.annotate(
        past_contacts=Count(Subquery(
            Contact.objects.values('id').filter(
                email_list=F('pk'),
                status='active',
                create_date__lt=start_date)
        )),
        past_deleted=Count(Subquery(
            Contact.objects.values('id').filter(
                email_list=F('pk'),
                status='deleted',
                modify_date__lt=start_date)
        )),
    )
    .values(
        'past_contacts', 'past_deleted',
    )
)

I had to change to use F instead of OuterRef because I realized that my model EmailList has id = HashidAutoField(primary_key=True, salt='...') was causing ProgrammingError: more than one row returned by a subquery used as an expression but I'm not completely sure about it.

Now the query works but sadly all counts are returned as 0