Table 1 ∣.

Transition probabilities of vagitypes during pregnancy over a 90-d window using a simplified Markov model

All samplesa	Lacto group (%)	L. iners (%)	G. vaginalis (%)	BVAB1 (%)	Other (%)a
Lacto group	75	7	2	1	15
L. iners	5	71	3	2	19
G. vaginalis	5	32	21	20	22
BVAB1	4	25	1	58	12
Other	16	31	8	9	36
All samplesb	Lacto group			L. iners	Otherb
Lacto group	75			9	16
L. iners	7			71	22
Other	13			34	53
Non-Africanb	Lacto group			L. iners	Otherb
Lacto group	83			2	15
L. iners	9			83	8
Other	27			14	59
Africanb	Lacto group			L. iners	Otherb
Lacto group	76			12	12
L. iners	1			76	23
Other	4			34	62

Probabilities over a 90-d window are shown as percentages. The initial vagitype is shown in the first column, and the transition frequency (%) to the subsequent groups is shown for each of the vagitype groups. In brief, the R package msm was used to fit a continuous-time Markov chain model for vagitype transitions. The model takes as input the subject, state, and gestational age in days for each sample. The states were Lacto, L. iners, BVAB1, G. vaginalis, and ‘other’ in the initial analysis^a, or Lacto, L. iners, and ‘other’ in the analysis examining ancestry differences^b. In each analysis, the Lacto group included the more protective Lactobacillus vagitypes (that is, L. crispatus, L. gasseri, and L. jensenii). Samples from women of African and non-African ancestry were included, and ancestry was modeled as a covariate. 95% confidence intervals for transition probabilities were used to determine whether there were statistically significant differences between ancestry groups. Ttransitions that exhibited large differences between the women of African and non-African ancestry are highlighted in bold.

^aModel examining transition of all 90 women across five vagitype groupings.

^bModel examining transitions in all women in the cohort across three vagitype groups. The same groupings are used to examine transitions in the 49 women of African or the 41 non-African ancestry.