Slow-ish Query Needs Some Love

I have a relatively straightforward query that by itself isn't that
slow, but we have to run it up to 40 times on one webpage load, so it
needs to run much faster than it does. Here it is:

SELECT COUNT(*) FROM users, user_groups
 WHERE users.user_group_id = user_groups.id AND NOT users.deleted AND
user_groups.partner_id IN
 (partner_id_1, partner_id_2);

The structure is partners have user groups which have users. In the
test data there are over 200,000 user groups and users but only ~3000
partners. Anyone have any bright ideas on how to speed this query up?

Here's the query plan:

 Aggregate  (cost=12574.53..12574.54 rows=1 width=0) (actual
time=2909.298..2909.299 rows=1 loops=1)
   ->  Hash Join  (cost=217.79..12566.08 rows=3378 width=0) (actual
time=2909.284..2909.284 rows=0 loops=1)
         Hash Cond: (users.user_group_id = user_groups.id)
         ->  Seq Scan on users  (cost=0.00..11026.11 rows=206144
width=4) (actual time=0.054..517.811 rows=205350 loops=1)
               Filter: (NOT deleted)
         ->  Hash  (cost=175.97..175.97 rows=3346 width=4) (actual
time=655.054..655.054 rows=200002 loops=1)
               ->  Nested Loop  (cost=0.27..175.97 rows=3346 width=4)
(actual time=1.327..428.406 rows=200002 loops=1)
                     ->  HashAggregate  (cost=0.27..0.28 rows=1
width=4) (actual time=1.259..1.264 rows=2 loops=1)
                           ->  Result  (cost=0.00..0.26 rows=1
width=0) (actual time=1.181..1.240 rows=2 loops=1)
                     ->  Index Scan using user_groups_partner_id_idx
on user_groups  (cost=0.00..133.86 rows=3346 width=8) (actual
time=0.049..96.992 rows=100001 loops=2)
                           Index Cond: (user_groups.partner_id =
(partner_all_subpartners(3494)))


The one obvious thing that everyone will point out is the sequential
scan on users, but there actually is an index on users.deleted. When I
forced sequential scanning off, it ran slower, so the planner wins
again.

Thanks for any help you can offer.