I can't speak to San Francisco specifically. But if it's anything like many other locations in the US, the problem isn't malice or indifference: it's that generating this data is vastly harder than you realize. The politicians get the data the same time you do: as soon as it's ready.

Here's one tiny true example, from one part of the pipeline in one particular location. A substantial amount of data enters the system as faxes. The faxes go to a room full of National Guard, who manually enter the data into computers, from whence it begins a complicated process of validation and de-duplication before it enters the main pipeline. You can imagine that this system doesn't scale particularly well as case counts rise.

At a broad scale, what's happening is that an immense amount of data is trying to enter a legacy system that was designed for less than one percent of its current load. Some of the data comes from sleek modern hospitals with state of the art medical informatics systems. And some comes from computer illiterate rural doctors, and some comes from nursing homes that had never reported lab results before Covid, and some comes from employers who test their employees, and some comes from private labs, and some comes from sovereign tribes that have complicated data sharing agreements with the state, and...

If I can find the time, I might write a post explaining in more detail how surveillance data is generated and processed. But for now, I assure you this problem is incredibly hard. Update: here's the post

Important disclaimer: my opinions are mine alone and I don't speak for any government agency.

It seems like the main alternative would be to have something like Alameda County's reporting, which has a couple days fewer lag at the expense of less quality control: https://covid-19.acgov.org/data.page?#cases.

It's really unclear to me that Alameda's data is more informative than SF's. (In fact I'd say it's the opposite--I tend to look at SF over Alameda even though I live in Alameda County.)

I think there is some information lost in SF's presentation, but it's generally less information lost than most alternatives on the market. SF is also backdating the data to when the tests were actually performed, thus being transparent about the fact that most test data is about what happened several days ago. Websites that claim to give you more up-to-date information are not actually doing so, they're just hiding this fact.

If you looked at the next 4 days in the time series it would probably look something like: 500, 200, 100, 100. Not because Omicron is abating but because most tests taken in the last 4 days haven't had time to be processed and recorded. I think if I was careful I could squeeze a small amount of information out of those numbers (e.g. based on whether the 500 was actually 400 or 600) but it would require a lot of work. I tried this in the past when working with some public health researchers and it's surprisingly hard to not fool yourself into thinking that cases are going down again when it's actually reporting lag.