sounds good hope to here more and like to see some pics .hope there is more trip reports fom kenyan

What about AIDS in Kenya?

Dcool

I'm going to post a Sex Guide on Kenya tomorrow. Though without pictures.. But I'll think something, I should get some.

About AIDS... It's a very big issue. First of all, currently there are vacinations on phase 3 in Kenya and Thailand. It means, that about 3 years from now the vacination are going to be available on the market. First 2 phases showed good response.
As of current, follow these guidlines: never fuck with pros without a condom. If she doesn't look decent - don't do oral sex without condom. Remember - getting HIV isn't very easy. For an average, it will take 1000 times to have sex with infected person untill man will become infected. It will be 200 times only if she has STD. It will take 50 times only if both of you have STD(s).
I have seen german staying in Kenya for twenty years and fucking everything which moves. They are still negative.

HIV vacinations? I've not heard of this and can't see how given the pathology of the virus. Got a link?

"Looks" has nothing do with whether one is infected or not.

Your stats are bogus.

The fact is that if you have unprotected sex with an infected female risk is apprx 1:200-500 depending on the study. This does not mean you have to screw 200-500 times to get infected. The risk remains constant for every act. U may get it with one exposure, you may never get it... It's a combination of virology, your biology, lady luck, a variety of exposure variables, etc...

It isn't all that easy to get as far as viruses go, but people do get it and the consequences are life and death.

As for oral sex, there is not one documented case of someone getting HIV from engaging in unprotected insertive oral sex.

-DM

Hi,
Read your report with interest. You write: "Dont waste your time in Nairobi..."
Questions:
1) Can you please elaborate? Is it because the girls are more expensive in Nairobi?
2) How long is the train journey from Nairobi to Mombasa?
3) Is there a lot of crime in Nairobi/Mombasa? Any precautions for foreigners visting Kenya?

Thanks!

This is a very, very interesting report. Is there a chance you could post scenic pictures? Like cambodia, this promises to be a exciting and aventorous place to visit.

I have to confess the issue on AIDS is worrysome. I watched in tv the other day that, in Angola, the rate of AIDS is super-high.

Nice report, looking forward to more

thanks

Ok!
I'll answer all questions here.

To Don Marco:

>Hiv vaccinations.
I had been in Nairoby National Hospital and spoken with the responsible for the program. Every vaccine is going thru few phases. First its' tried on some animals, then on monkeys. Thereafter 3 years Phase 1 - they vaccinate NO RISK group and constantly monitor them. Then Phase 2 - there is broader involment and they start to check the effectiveness too. Then Phase 3 - they give it to High Risk group and check for the effectiveness. Currently they had started Phase 3 I believe.
The HIV vaccination initiatives are being developed in USA, UK, Thailand and Kenya. That's what I heard. The one in Kenya I had seen and I was just about to volunteer myself, but then I had to leave Kenya.

>"Looks" has nothing do with whether one is >infected or not.
Directly yes. Indirectly - no. If the girl look decent, she initiate using of condoms, of course you may not be sure she is negative, there are just more chances she is negative then someone who look dirty, someone who gives you an expression of a street whore. Got my point?

>Your stats are bogus.
>The fact is that if you have unprotected sex with >an infected female risk is apprx 1:200-500 ...
So you are talking about 1:500. I was talking about 1:1000, but took consideration of STD's reducing it to 1:50.. In average I would agree with you on 1:250-500

>It isn't all that easy to get as far as viruses >go, but people do get it and the consequences are >life and death.
Well, I believe that you may not die from HIV if you are healthy otherwise, because of:
a) You will maintain your live on ARVs for about 20-30 years.
b) During this time you hope our sientists will find a cure.

>As for oral sex, there is not one documented case >of someone getting HIV from engaging in >unprotected insertive oral sex.
Well, may be there are undocumented ones


TO BKK GURU:
Read your report with interest. You write: "Dont waste your time in Nairobi..."
Questions:
1) Can you please elaborate? Is it because the girls are more expensive in Nairobi?
- No. The life there is faster. The girls are harshier. The background of Nairobi is generally not nice for having fun, as it's more for making business. The distances you have to cover are greater and therefore it's alittle bit tiresome. There are more carjacking and other crimes. The girls there are more serious.
The price could be the same, since there is no standards of prices. You may find a short time in Nairobi as cheap as 200ksh. Which is the same as in Mombasa.
And, in fact, the Nairobi girls (not prostitutes!) are VERY cute, clever and decent looking. It's just that they are always busy and it's not fun to play with them. But it's mostly the background. Once you find Nairobi girls in Mombasa - woila!

2) How long is the train journey from Nairobi to Mombasa?
- It starts 7pm (inshalla) and reaches at 9am.

3) Is there a lot of crime in Nairobi/Mombasa? Any precautions for foreigners visting Kenya?
- In Nairobi don't go outside of your residential places after darkness. In Mombasa - it's ok, you may walk around at any time.

TO ANDRESB.
This is a very, very interesting report.
-> Then wait for the full release It will include more.

Is there a chance you could post scenic pictures?
-> Well. Especially of the moderator of this place will get my account upgraded so *I* can see photos of other members as well But I have very few photos, anyway.

Like cambodia, this promises to be a exciting and aventorous place to visit.
> I guess so, though I never been to Cambodia.

Nice report, looking forward to more.
> It was the beta version here. The full one is coming.

BTW: ABout HIV/AIDS.
There is PEP treatment available. (Post Explosure Prophylahis). Usually the duration is 4 weeks and usually its given to raped women during 3? days after the intercourse. I was always thinking if it's possibel to use it for BB mongering? Any ideas?

"The HIV vaccination initiatives are being developed in USA, UK, Thailand and Kenya. That's what I heard."

Comment: First I've heard of it and it seems contrary to logic-- have you seen published results in a medical journal?


"If the girl look decent, she initiate using of condoms, of course you may not be sure she is negative, there are just more chances she is negative then someone who look dirty, someone "

Comment: how does looking decent equate to using condoms and being negative? on the contrary, how does looking "dirty" (are u refering to lack of pers. hygeine?) equate to increased risk?


"So you are talking about 1:500. I was talking about 1:1000, but took consideration of STD's reducing it to 1:50.. In average I would agree with you on 1:250-500"


Comment: The point I was making was that you mis-used or misunderstood statistical theory. If odds are 1:500, then you do not "on average fuck 500 times before getting infected" (e.g., your original logic). Risk per exposure is constant for each episode and does not increase over time.



"Well, may be there are undocumented ones"

Comment: possibly, but highly unlikely.

Don Marco:
There was a report of 2004/09 Skm's China Trip Report. There was two girls from massage parlour. You said they aren't chinese? Could you e-mail their photos and say your opinion who they look alike are?

Mm. I have replied to your message, but I don't see it here now..

Anyway, I'll retype the reply from memory

Comment: First I've heard of it and it seems contrary to logic-- have you seen published results in a medical journal?

Hm.. In my original reply i written you the links, but now I don't want to make a second turn of looking. Just google: Nairobi KAVI, Thailand HIV vaccination..
Why is it contrary to logic?


Comment: how does looking decent equate to using condoms and being negative? on the contrary, how does looking "dirty" (are u refering to lack of pers. hygeine?) equate to increased risk?

This one is a little bit difficult for me to explain.

Comment: The point I was making was that you mis-used or misunderstood statistical theory. If odds are 1:500, then you do not "on average fuck 500 times before getting infected" (e.g., your original logic). Risk per exposure is constant for each episode and does not increase over time.

Well. First about numbers. When I talked to the sientist working on vaccination, he told me 1:1000. In Israel the official point is 1:300. I guess that 1:500, 1:300 is selected as safest by the media, but the true one is 1:1000.

Second, I don't get your logic. I agree that "Risk per exposure is constant for each episode" so how it can't increase over time?
When you BB infectd female one time your risk of getting HIV is 1 out 1000. When you BB her for the second time its 2 out of 1000. If you bb'ed her 500 times - it's 50/50 that you are infected. Is my logic wrong?

Also, my theory is like this:
1) Acute and visible STDs dramastically increase chance of infection.
2) It's common for HIV infected lady to be infected by STD, being it active or cured.
3) If there would be no STDs there would be no HIV epidemic. Why? Because 1:1000 means that an average african should BB his infected female for 3 constant years in order to get infected (they do it usually 1 time per day). Cconsidering that initially there were very few people infected from an unknown cause and then they started to spread the virus around, it would take centuries for this disease to become epidemic. Of course females are infected easier then man (by the way, if media says 1:250-500 for man, what do they say for females?), but anyway, I believe STDs, Warts are making chances of 1:50, making HIV epidemic.

When you taking a random female to BB you aren't sure whether she is infected or not. Therefore you may use the prevailence rate for this country. Let's say you take a lady in a country where 1 out 20 girls is infected. Then, if neither you or the girl don't have STDs your chance of becoming infected is 1:20000. Got my point?
You may probably know if you have STDs by checking blood, urine and visible. What about the lady? Before BBing her, try to take a look at her pussy and around. Look for any dots, bad odour, swellings, pus. If you see any, don't BB with her unless you went with her for checking first.
If indeed she has got no visible signs, you may not yet be sure she has no STDs. Therefore, giving the benefit of doubt, you would consider your chance of infection 1:10000 in this theoretical case.
Also, it would be nice for Monger if there would be "Use yourself HIV and Major STD KIT". Then you would prick the ladies finger and get fast results of who she is.
NOTE: I find warts are quite troublesome. I wonder if there are any tests to find them in ladies.

Second, I don't get your logic. I agree that "Risk per exposure is constant for each episode" so how it can't increase over time?
When you BB infectd female one time your risk of getting HIV is 1 out 1000. When you BB her for the second time its 2 out of 1000. \Is my logic wrong?



Yes-- your arithmetic is wrong. The first BB is 1/1000, the second time is 1/1000, and so on. It is not cumulative.


Good luck and happy mongering,


DM

WARNING THE FOLLOWING IS TEDIOUS SIMPLE PROBABILITY THEORY

OK, a quick lesson on the probability experiment being discussed here. Let's make this simpler by assuming your are going to repeatedly have vaginal intercourse with an HIV infected women UNTIL YOU BECOME INFECTED. Let's make the probability of infection .4 and also assume that each time you fuck are you are not infected the probability is still 40%. Also let i be the actual session number you get infected.

The probability you are infected on your first fuck is 40%. So the probability you are infected on your first session, denote Pr(i=1), is 40%.

What is the probability you are infected in your second session? Well that means you DID NOT get in infected in your first session, and then did get infected in the second session. The probability you did not get infected in the first session is .6 and then the subsequent probability of then getting infected in the second session is .4. So the probability of getting infected in the second session is the probability of not getting infected the first opportunity times the probability of getting infected in the second session conditional upon being HIV negative before the second session, or simply Pr(i=2)= .6*.4 = .24.

Now what is the probability you have been infected BY THE TIME YOU HAVE DONE TWO SESSIONS?
The way you can be infected after two sessions is that you were infected in session one or in session two. So the probability of being infected after two fucks is the probability of being infected in session 1 plus the probability of being infected in session 2, or Pr(i <= 2) = Pr(i=1) + Pr(i=2) or 64%.

In our little experiment, what is the probability you catch the infection in your third session? Well that means your did not get infected in session 1 or 2 and then did get infected in session 3. Well that is simple
Pr(i=3) = (.6)*(.6)*(.4) or 9.6%. Also the probability of being infected after three sessions is Pr(i=1) + Pr(i=2) + Pr(i=3) or 73.6%.

The type of probability distribution we are describing here is called the Geometric distribution. For the general case where p = probability of infection conditional upon not being infected, and where i is the session number in which one is first infected the probability for session number x to be the one in which the infection is first contracted is Pr(i=X)= (1-p)^(X-1)*p. To get the probability you will be infected after z number of sessions you must add up all the probabilities of being infected in exactly each of the first z sessions.

So how many sessions on average will our doomed monger have before he contracts the infection. All the calculations reduce down to the intuitive results 1/p. So if the chance is one out of a thousand we would expect the monger to get infected on his 1000th session. But in fact he could catch the infection in session 1 or not until session 1,000,000.

To get a better feel for what the probability is of being infected after any x number of sessions with a fixed transmission rate you can look at a graph of the cumulative summation of probabilities. The summation is called the CDF (Culmative distribution function) and you can generate a graph of the for different transition probabilities and the number of sessions you do at the following website:
http://www.mechmat.univ.kiev.ua/probability/Projects/StatGraph/GeometricGraph.html

If this doesn't bore you to tears. We can next address the issue, "So my HIV test, with 98% accuracy, came back positive what is the REAL probability I am HIV positive?" Hint, it isn't 98%!

Let me explain this differently:

Each time you boff a HIV infected person represents, roughly, a 1:1000 chance.

Stated another way, EACH TIME you fuck it's like dumping a box full of dice (about 167 of them) on the floor. Is it POSSIBLE to roll all boxcars, but how PROBABLE is it. Just dumping that ONE box on the ground is not likely to yield those results.

Now, let's say you dropped that same box twice a day for a year. This means EACH TIME you dumped the box is a completely new event (provided you didn't get all 6s on a previous roll) and so another 1:1000 chance of earning a faster ride into the unknown.

As MX stated, you could roll the full batch of 6s on the VERY FIRST ROLL. This is 1 of 1002 POSSIBLE outcomes. Taken as a single event, it sure doesn't SEEM like a big chance. Now, keep rolling those dice and see how much you sweat box after box after box after box after box...

It's possible to fuck once, and get HIV. It's also possible to fuck a million times and NEVER get it. How willing are you to roll 'dem bones?

In the immortal words of Harry Callihan: "you've got to ask yourself one question: Do I feel lucky? Well, do ya punk?"

E

Epi-- exactly the point I was trying to make...

DM

I was simply trying to restate in a clearer, more graphic form the point made by you and MX.

However: "When you BB infected female one time your risk of getting HIV is 1 out 1000. When you BB her for the second time its 2 out of 1000. Is my logic wrong?"

It's been a loooOOOOOooooong time since my stats and research methods classes, but what MX is saying is, effectively, your logic is indeed wrong. This is also what I tried to display, but not in the same manner he used.

Using your logic:

Fuck once: 1:1000
Fuck twice: 2:1000
Fuck one thousand: 1000:1000 = 1:1 = guaranteed infection.

Possible - adj: Capable of happening, existing, or being true.

It is POSSIBLE your lottery ticket will be a winner.

probable - adj: Likely but not certain to be or become true or real.

It is PROBABLE your lottery ticket will become recycled toilet paper.

Each event is, indeed, a low probability crapshoot.

Applying these definitions in a normal distribution:
Mathmatically, it is POSSIBLE to fuck an infected person once and get infected, but not PROBABLE.

Applying this to the right tail of the distribution: Mathmatically, it is also POSSIBLE to go five lifetimes of fucking eight times a day without getting infected, however, not PROBABLE.

Does that make sense? It's been quite some time since I dusted off the ol' cerebrum.

E

DM's opinion:
Yes-- your arithmetic is wrong. The first BB is 1/1000, the second time is 1/1000, and so on. It is not cumulative.

MX's opinion:
Not so clear to me, because he started from 40% probability.
Thereafter he refers to a site in Kiev, which is funny enough is a town where I was born MX's, ti govorish po russki?
Anyway, could you please take 1:1000 and using SIMPLE PROBABILITY THEORY give us answer for 2nd BB, for 3rd bb, for 500's bb and for 1000's BB?

EPI's opinion:
He doesn't give any clear answer, but generally agrees with DM?

I have a feeling DM and EPI are wrong. MX may be right, but let us see the real numbers.

DM and EPI, let me ask you a question.. You are constantly playing LOTO. The LOTO is where you have to selected a number 1..1000. If you guessed the right number, you are winner. Don't you realise, that as more oportunities you will be given the more chance for you OVERALL to become the winner?

Anyway, I look forward to get an answer from MX. Guys from Russia are good mathematicians.

Epis anaolygy is best but he's playing with way to many dice in his box. 167 dice in your box is cheating. Just a teensy little flaw with the Epimath In reality the odds of a man contracting HIV from one unprotected vaginal sex act with an HIV positive woman it's much closer to the odds of shooting all boxcars with only 4 dice. Throw in a 5th dice and youd pretty much come up with your odds of a status unknown person in Kenya. Throw in a 6th dice for your odds with a status unknown person in US or Mexico.

Mr. Blackion, please dont get distracted on statistics, we are waiting on your report.

Grab a cup of coffee and rechant all those moments you spent with those fine brown girls. Then write your report and post it here.

Thank you in advance!

Man MongerX's post gave me flashbacks of taking the LSAT exam....my head was spinnin'.

One other thing AndresB...I'm guessing he didn't have too much time with brown girls in Kenya. From the Kenyan's that I have met, they are as black as they come. Can't say I have seen an attractive Kenyan girl and I love black girls but Somalian girls...that's a different story...many runway models from that country and I can see why...very exotic. I mean look how great David Bowie scored with Iman...she is still smokin' hot.

The point I think we are crossing wires on is this: in events such as this, you have two ways of measuring probabilitiy:

1. As a population-- that is in totality. For example risk is a f(a combination of all individual risks). MongerX illustrated this with his post.


OR

2. Access risk for each individual act-- what epi and I illustrated. For example, if the risk is 1:1000 per act, it is constant since the possible outcomes remain the same for every incident. So my risk of getting HIV when screwing a gal with HIV is 1/1000 today. If I screw her again tomorrow I still have a 1:1000 chance, and so on. Perhaps I'm unlucky and draw the short straw, perhaps I'm lucky and never draw the straw...


Your lotto example is exactly why I said your logic was wrong. When you play a lotto #, you remove that possibility from the population of possible outcomes, if you play 2 #s you remove 2 possiblities, thereby increasing odds... this is exactly why the two situations are completely different....

'nuf said-- if we haven't made our point by now then it wasn't meant to be... After all this idle chat, I'm ready to go bareback a few times!

Actually DM, EPI, and Myself are all correct. DM is correct in asserting than whenever an HIV negative male sessions with an HIV+ female, the probability he gets infected in THAT SESSION is always the same regardless of whatever has happened in the past.

Epi's excellent example (while have way too many diea) is very simple demonstration that while the probability of getting infected in any one session is small, If one rolls the die many times (pun intended) the probability of getting infected at some point grows to be significant.

I tried to provide the machinery to allow one to calculate the probability of being infected after any number of sessions.

With some simple calculations here are some of the probabilities (expressed in percentages) of becoming infected if you ALWAYS session with HIV+ female and the probability of transmission is 1 in a thousand

# of sessions - Probability
10(Wild Weekend) - 1%
25(A good week) - 2.5%
365(A year) - 30.6%
1000(A monger career) - 63.2%
1825(5 years) 83.9%
3650 (10 years) 97.4%
10000(Wilt) 99.999%

Now let's do the calculations with the same transmission rate, but assuming that you bang a different Ho' each time and that 5% of the Ho' population is HIV+

# of sessions - Probability
10(Wild Weekend) - .05%
25(A good week) - .12%
365(A year) - 1.8%
1000(A monger career) - 4.9%
1825(5 years) 8.7%
3650 (10 years) 16.7%
10000(Wilt) 39.3%

Blackion, I am not Russian but am of Russian heritage. I posted that website because it has a way you can calculate these numbers (and visualize them) you whatever transmission probabilities you wanted.

MongerX: I guessed you aren't Russian, just gave it a try.

AndresB and Blazers: Most of the ladies are black with some brownish appearence. Their aren't totally black. Around 20% ladies are fairly brown. Somalie ladies are light-brown, very exotic and beautiful. Somali ladies known for the fact that most of them have their clitter cut off as part of their traditions, but despite it they are known to be very hot and passionate and difficult to get.

DM: Well, whatever. Let the theory never kill the action .

MX: Well, you have shown yourself, that overall your chance of become infected is dependent upon the number of BBs you performed, therefore it's indeed cumulative.
# of sessions - Probability
10(Wild Weekend) - 1% = 1:100
>10:1000 = 1% = 1:100 and it's the same way I calculated it before. How did you come to the same result?
25(A good week) - 2.5% = 25:100

I was looking forward for your explanation of as you did it in the first post, but please, don't use percentage and use only those examples:
1:1000, 2:1000, 3:1000, 500:1000, 1000:1000, 1100:1000.

I'm going to post a Guide to Ethiopia in two days with photos. That's gonna be smokin'.

I would suggest anyone with an interest in Africa read "Native Stranger" and "Dark Star Safari" the former written by a black man, the latter by a white man.

I would love to visit East Africa, but wouldn't dream of doing it alone. Apparently great times to be had, but danger lurks around every corner. Don't know if I have the "huevos" for that at my age. Ah the stuff that dreams are made of.

Excellent report. Looking forward to reading more...

The problem here is that people are interchanging Odds & Probability.

DM is talking odds and calling them probabilities

EPI and Blackloin are talking probabilities.

Odds do not change for a certain event, as each event is seen as independant. That is why the Casino will ALWAYS take your money in the long run. The odds of a game don"t change no matter how many times you roll the dice and in all casino games the odds are in the houses favor.
The probability of an outcome is effected by what has happened before, because it is one in a series of connected events.

An easy analogy is flipping a coin. The odds are 1:1 or 50/50 every time you flip a cion(DM). If you flip a coin 100x and the results are 100 heads. The odds are still 50/50 the 101st time you flip the coin, however the probablity that it will come up heads 101st time are next to zero(Epi,Blacklion).

Therefore, the odds of becoming infected form a BB session with an HIV+ female do infact remain the same for each session(1:500,1:1000 whatever). However the probability of getting infected increase with each BB session with an HIV+ female.

The answer is still the same, use a condom

Damn, If i had only read this thread when I was in college, I could have CLEPEd out of statistics.....! Good stuff though

Rat,

Check your ole books before you start defining what I say:

Using the Bernoulli model each sexual contact such that is capable of transmitting the virus from an infected person to his or her partner is treated as a Bernoulli trial. The single-contact "probability" of HIV transmission from an HIV-infected person to a previously uninfected partner is called the per-contact infectivity of HIV.

I prefaced some time ago that given the low #s of exposure episodes combined with lows prob per incident risk, that I view risk to be = to the per incident risk vs. using the cumulative model (1-(1- prob)n).

Are you adding anything to this or just trying to tell me what I said last week?

Here is some food for thought. Suppose someone has a positive result on an HIV test. Given that these tests are about 99% accurate (in other words 1% of the time the test comes back positive for some who is negative.) you would think that the odds you are HIV+ is 99 out of 100. However, in fact it is much less than 50%.

Imagine there are 100,000,000 males in the population and that .6 of the population is HIV+. In other words, 600,000 males are HIV+ and 99,400,000 males are HIV negative. Now let's assume that the each of the truly HIV+ males will test positive. That is 600,000 positives.

What about the HIV negative males' test results? With 99% accuracy, you will observe roughly 994,000 positive test results. So if every male is tested we would observe about 1,594,000 positives.

Now if someone test positive for HIV, he is equally likey to be any of the 1,594,000 postives. So the probability that a male who test positive is truly HIV+ is the fraction of the 1,594,000 positives that are true positives. This fraction is about 38%!

Gregorio:
Africa nowdays isn't dangerous. While in Mombasa I see men of all types up to the age of 70 going with young ladies. Not it to be enough, I see many women around their forties going with fine young black men while paying them money, buying for the motocycles, etc. I just wonder if there is another clubhombre for women overthere

right, the chance of throwing all 6 o 4 dices is 1/6*6*6*6 which is a bit smaller chance then 1/1000. Like a version of Russian roulette.


Of course, this is a statistical model for small numbers. In reality, there is a certain small percentage of the population that is simply immune to HIV. But you can not be sure you are in that percentage of immune people.


There is another large percentage, probably the African races, who seem to catch it especially easy.

So the statistical model is crude and cannot really be extrapolated to thousands of sex acts. But it gives you some vague idea of how things work.