11-PMTCT.Rmd

---
editor_options: 
  markdown: 
    wrap: 72
---

\blandscape

# PMTCT

## Host Country Context

```{r echo=FALSE, results='asis'}
sheet_name <- "PMTCT"
section <- "Partner Country (P.C.) Context"
columns <- col_seq("F", "Q")
data <- prepare_table_data(sheet_name, columns)
for (t in table_seq(data, max_col = 3)) {
  make_table(t, section)
  }
```

### DATIM Import

The following data will NOT be imported into DATIM but will appear in the COP Dossier from this section of the
Target Setting Tool:

-   **Host Country PMTCT_STAT_SUBNAT (D) - \# New ANC clients (FY24)**
    $PMTCT\_STAT\_SUBNAT.D.T\_1$

-   **Host Country PMTCT_STAT_SUBNAT (N) - Known Positive (FY24)**
    $PMTCT\_STAT\_SUBNAT.N.Known.Pos.T\_1$

-   **Host Country PMTCT_STAT_SUBNAT (N) - New Positive (FY24)**
    $PMTCT\_STAT\_SUBNAT.N.New.Pos.T\_1$

-   **Host Country PMTCT_STAT_SUBNAT (N) - New Negative (FY24)**
    $PMTCT\_STAT\_SUBNAT.N.New.Neg.T\_1$

-   **Host Country PMTCT_ART_SUBNAT (D) - HIV-positive pregnant women (FY24)**
    $PMTCT\_ART\_SUBNAT.D.T\_1$

-   **Host Country PMTCT_ART_SUBNAT (N) - Already on ART (FY24)**
    $PMTCT\_ART\_SUBNAT.N.Already.T\_1$

-   **Host Country PMTCT_ART_SUBNAT (N) - New on ART (FY24)**
    $PMTCT\_ART\_SUBNAT.N.New.T\_1$

### Instructions

1.  Review data for the following columns, all of which come from
    corollaries on the Cascade tab. Follow hyperlinks to navigate to the
    source of this data:

    a.  Host Country Estimated Female Population (FY24)

    b.  Host Country Estimated PLHIV (FY24)

    c.  Host Country Estimated HIV Prevalence (FY24)

    d.  Host Country Estimated TX_CURR_SUBNAT (FY24)

    e.  Host Country Estimated ART Coverage (FY24)

2.  If using Spectrum as the source for Host Country Context data, the
    following columns will initially be populated based on data from the
    Spectrum export dataset added to the Spectrum tab of the Target Setting Tool.
    Review these and return to Spectrum to adjust assumptions there as
    needed. With approval by your PPM and assigned DUIT Liaison, you may
    also identify and use another source for this data.

    a.  Host Country PMTCT_STAT_SUBNAT (D) - \# New ANC clients (FY24)

    b.  Host Country PMTCT_STAT_SUBNAT (N) - Known Positive (FY24)

    c.  Host Country PMTCT_STAT_SUBNAT (N) - New Positive (FY24)

    d.  Host Country PMTCT_STAT_SUBNAT (N) - New Negative (FY24)

    e.  Host Country PMTCT_ART_SUBNAT (D) - \# HIV-positive pregnant
        women (FY23)

    f.  Host Country PMTCT_ART_SUBNAT (N) - Already on ART (FY24)

    g.  Host Country PMTCT_ART_SUBNAT (N) - New on ART (FY24)

## PMTCT: New ANC Clients

### PMTCT_STAT (D) and PMTCT_STAT_SUBNAT (D)

**PMTCT_STAT (D):** Number of new ANC clients in reporting period.

```{r echo=FALSE, results='asis'}
sheet_name <- "PMTCT"
section <- "New ANC Clients"
columns <- col_seq("R", "V")
data <- prepare_table_data(sheet_name, columns)
for (t in table_seq(data)) {
  make_table(t, section)
  }
```

### DATIM Import

The following data points will be imported into DATIM from this section:

-   **PMTCT_STAT (D) (FY25)** $PMTCT\_STAT.D.T$

-   **PMTCT_STAT_SUBNAT (D) (FY25)** $PMTCT\_STAT\_SUBNAT.D.T$

### Instructions

1.  For historical context, review FY24 targets for PMTCT_STAT (D),
    reflected in the Target Setting Tool per data reported in DATIM.

2.  Review and adjust the Expected change in new ANC clients, which
    should help indicate whether there is an anticipated change in the
    number of women presenting to ANC compared to FY24. This is
    defaulted at 0%, though this reflects no suggestion of strategy from
    S/GAC. Adjust these growth rates to reflect intentional,
    data-driven, strategic programming. Values can be negative or
    positive percentages in this column, which will decrease or increase
    the FY24 target for PMTCT_STAT (D) respectively. (If the expected
    number of women presenting in ANC for FY23 is the same as FY22, the
    value in column F would be "0%". If it increased by 50%, the value
    would be "50%". If the number should decrease by 20%, enter "-20%".)

3.  Review FY25 targets for PMTCT_STAT (D), which is calculated by
    multiplying the Expected change in new ANC clients (set in step 2)
    by the lesser of either the "Host Country PMTCT_STAT_SUBNAT (D) - \#
    New ANC clients (FY24)" set in the Host Country Context section, or
    the PMTCT_STAT (D) FY23 targets from DATIM. In the case services are
    planned in FY25 where these were not provided in FY24, you may
    manually enter FY25 targets in this column.
    
4.  Review H.C. % ANC clients served at PEPFAR-supported sites (FY24) (%)
    which will be calculated by dividing historic PMTCT_STAT (D) (FY23)
    target by the column K H.C. New ANC Clients (FY23). This percentage
    can be modified if the calculation does not produce the proper coverage.
    
5.  Column V H.C. PMTCT_STAT_SUBNAT (D) (FY25) target will divide the FY25 
    target set for PMTCT_STAT (D) and the % calculated in step 4.

## PMTCT: ANC1 Testing - PEPFAR

### PMTCT: PMTCT_STAT (N)

**PMTCT_STAT (N):** Number of pregnant women with known HIV status at
first antenatal care visit (ANC1) (includes those who already knew their
HIV status prior to ANC1).

```{r echo=FALSE, results='asis'}
sheet_name <- "PMTCT"
section <- "ANC1 Testing - PEPFAR"
columns <- col_seq("W", "AD")
data <- prepare_table_data(sheet_name, columns)
for (t in table_seq(data, max_col = 4)) {
  make_table(t, section)
  }
```

### DATIM Import

The following data points will be imported into DATIM from this section:

-   **Total PMTCT_STAT (N) (FY25)** $PMTCT\_STAT.N$

-   **PMTCT_STAT (N) Known HIV Status, Positive (FY25)**
    $PMTCT\_STAT.N.KnownPos.T$

-   **PMTCT_STAT (N) Newly Tested, Positive (FY25)** $PMTCT\_STAT.N.New.Pos.T$

-   **PMTCT_STAT (N) Newly Tested, Negative (FY25)** $PMTCT\_STAT.N.New.Neg.T$

### Instructions

1.  Review FY23 Results for (a) Estimated % ANC1 clients with already
    Known HIV Positive status, and (b) Estimated Positivity Rate among
    Newly Tested ANC1 clients.

2.  Review FY25 projections for (a) Estimated % ANC1 clients with
    already Known HIV Positive status, and (b) Estimated Positivity Rate
    among Newly Tested ANC1 clients. These data default to remain static
    from related FY24 rates added to the Host Country Context section of
    this tab. Where these are unavailable, these instead use FY23
    results trends. In either case, these can be adjusted as necessary
    with approval by your PPM and DUIT Liaison. Red highlights indicate
    percentages over 100%; yellow highlights indicate percentages
    different from FY23 results. See below for additional information.

3.  Review "Total PMTCT_STAT (N)", which will display the numerator
    value for PMTCT_STAT based on the multiplication of "PMTCT_STAT (D)"
    and the "Targeted testing coverage of ANC1 clients (FY24)". To make
    changes to the PMTCT numerator, adjust either the PMTCT denominator
    or the desired testing coverage.

4.  Review PMTCT_STAT Known HIV Status, Positive, which will be
    calculated based on multiplying Total PMTCT_STAT (N) by the
    Estimated percent of ANC1 clients already Known HIV Positive.

5.  Review PMTCT_STAT Newly Tested, Positive, which will be calculated
    based on first removing the PMTCT_STAT Known HIV Status, Positive
    cohort from Total PMTCT_STAT (N), then by multiplying this value by
    the Estimated Positivity Rate among Newly Tested ANC1 clients.

6.  Review PMTCT_STAT Newly Tested, Negative, which will be calculated
    as the remainder of Total PMTCT_STAT (N) less both PMTCT_STAT Known
    HIV Status, Positive and PMTCT_STAT Newly Tested, Positive.

### FY25 Projected Known Positivity and New Positivity Rates

In projecting rates of Known and New positivity for PMTCT_STAT ANC1
clients, the COP21 Target Setting Tool relies first upon Host Country Context
estimates, provided by Spectrum or another approved source, and where
this data is unavailable, upon PEPFAR FY22 results obtained from DATIM
on the date of the Target Setting Tool's generation, as documented on the Home tab.
These rates are calculated from Host Country Context data as follows:

$$
{Estimated\ \%\ ANC1\ clients\ already\ Known\ HIV\ Positive}_{t}\  = \\
\frac{{PMTCT\_ STAT\_ SUBNAT.N.Known.Pos.}_{t - 1}}{{PMTCT\_ STAT\_ SUBNAT.D}_{t - 1}}
$$

$$
{Estimated\ Positivity\ Rate\ among\ Newly\ Tested\ ANC1\ clients}_{t}\  = \\
\frac{{PMTCT\_ STAT\_ SUBNAT.N.New.Pos.}_{t - 1}}{{PMTCT\_ STAT\_ SUBNAT.D}_{t - 1}\  - \ {PMTCT\_ STAT\_ SUBNAT.N.Known.Pos}_{t - 1}}
$$

## PMTCT: ANC1 Testing - Host Country
### PMTCT: PMTCT_STAT_SUBNAT (N)

```{r echo=FALSE, results='asis'}
sheet_name <- "PMTCT"
section <- "ANC1 Testing - Partner Country"
columns <- col_seq("AE", "AH")
data <- prepare_table_data(sheet_name, columns)
for (t in table_seq(data)) {
  make_table(t, section)
  }
```

### DATIM Import

The following data points will be imported into DATIM from this section:

-   **Host Country PMTCT_STAT_SUBNAT (N) - Known Positive (FY25)**
    $PMTCT\_STAT\_SUBNAT.N.Known.Pos.T$

-   **Host Country PMTCT_STAT_SUBNAT (N) - New Positive (FY25)**
    $PMTCT\_STAT\_SUBNAT.N.Known.Pos.T$

-   **Host Country PMTCT_STAT_SUBNAT (N) - New Negative (FY25)**
    $PMTCT\_STAT\_SUBNAT.N.New.Neg.T$

### Instructions

1.  Review the Total PMTCT_STAT_SUBNAT (N) that is calculated using the
    target set in the previous section for PMTCT_STAT_SUBNAT (D) (FY25)
    and Targeted testing coverage of ANC1 clients (FY25) (%) from the
    PMTCT_STAT (N) section. This will be used to calculate the FY24
    targets for the remainder of this section

2.  Review Host Country PMTCT_STAT_SUBNAT (N) - Known Positive (FY25)
    which will be calculated as the product of the Total
    PMTCT_STAT_SUBNAT (N) and Projected % ANC1 clients Known HIV
    Positive (FY24) (%). Adjust this percentage from the previous
    section to make changes to this target.

3.  Review Host Country PMTCT_STAT_SUBNAT (N) - New Positive (FY25) in
    the same manner as it uses the SUBNAT Numerator and Est. Positivity
    Rate among Newly Tested ANC1 clients (FY25) (%). Adjust this
    percentage from the previous section to make changes to this target.

4.  Review Host Country PMTCT_STAT_SUBNAT (N) - New Negative (FY25)
    which will be calcuated as the remainder of Host Country
    PMTCT_STAT_SUBNAT (N) - Known Positive (FY25), less Host Country
    PMTCT_STAT_SUBNAT (N) - Known Positive (FY25) and Host Country
    PMTCT_STAT_SUBNAT (N) - New Positive (FY25).

## PMTCT: ART - PEPFAR
### PMTCT: PMTCT_ART (N)

**PMTCT_ART (N):** Number of HIV-positive pregnant women who received
ART to reduce the risk of mother-to-child transmission during pregnancy.

```{r echo=FALSE, results='asis'}
sheet_name <- "PMTCT"
section <- "ART - PEPFAR"
columns <- col_seq("AI", "AK")
data <- prepare_table_data(sheet_name, columns)
for (t in table_seq(data)) {
  make_table(t, section)
  }
```

### DATIM Import

The following data points will be imported into DATIM from this section:

-   **Already on ART (FY25)** $PMTCT\_ART.Already.T$

-   **New on ART (FY25)** $PMTCT\_ART.New$

### Instructions

1.  Review Targeted ART Linkage Rate for linkage between PMTCT_STAT (N)
    Newly Tested, Positive and PMTCT_ART New on ART. This rate is locked
    in step with ART Linkage Rates set on the Cascade Tab, which default
    to 95%; return to that tab to adjust this rate, though note that
    this will alter linkage rates across all modalities.

2.  Review modeled targets for PMTCT_ART (N) Already on ART. For the
    purposes of COP21 target setting in the Target Setting Tool, FY24 targets for
    PMTCT_ART Already on ART are set assuming that 100% of those ANC1
    clients with already known HIV positive status are already on ART.

3.  Review modeled targets for PMTCT_ART New on ART, which is calculated
    by multiplying PMTCT_STAT (N) Newly Tested, Positive by the Targeted
    ART Linkage Rate.

## PMTCT: ART - Host Country
### PMTCT: PMTCT_ART_SUBNAT

```{r echo=FALSE, results='asis'}
sheet_name <- "PMTCT"
section <- "ART - Host Country"
columns <- col_seq("AL", "AN")
data <- prepare_table_data(sheet_name, columns)
for (t in table_seq(data)) {
  make_table(t, section)
  }
```

### DATIM Import

The following data points will be imported into DATIM from this section:

-   **Est. Host Country \# HIV-positive pregnant women (FY25)**
    $PMTCT\_ART\_SUBNAT.D.T$

-   **Est. Host Country \# HIV+ Pregnant Women Already on ART (FY25)**
    $PMTCT\_ART\_SUBNAT.N.Already.T$

-   **Est. Host Country \# HIV+ Pregnant Women New on ART (FY25)**
    $PMTCT\_ART\_SUBNAT.N.New.T$

### Instructions

1.  Review Est. Host Country \# HIV-positive pregnant women (FY25). This
    is the summation of FY25 Targets set in the PMTCT_STAT_SUBNAT (N)
    Section for Host Country PMTCT_STAT_SUBNAT (N) - Known Positive
    (FY24) and Host Country PMTCT_STAT_SUBNAT (N) - New Positive (FY24).

2.  

## PMTCT: HTS_TST: PMTCT Post ANC1

**HTS_TST:** PMTCT Post ANC1: Includes pregnant or breastfeeding women
who receive a test POST ANC1, this includes women who are tested later
in pregnancy (\>ANC2), during labor & delivery (L&D), and while
breastfeeding.

```{r echo=FALSE, results='asis'}
sheet_name <- "PMTCT"
section <- "Post ANC1"
columns <- col_seq("AO", "AU")
data <- prepare_table_data(sheet_name, columns)
for (t in table_seq(data, max_col = 4)) {
  make_table(t, section)
  }
```

### DATIM Import

The following data points will be imported into DATIM from this section:

-   **HTS_TST PMTCT Post ANC1, Positive (FY25)** $HTS\_TST.PostANC1.Pos.T$

-   **HTS_TST PMTCT Post ANC1, Negative (FY25)** $HTS\_TST.PostANC1.Neg.T$

### Instructions

1.  Review and adjust the Total eligible for Post ANC1 retesting, which
    is initially set equal to the number tested and found negative in
    initial ANC1 testing.

2.  Review and adjust the Yield for PMTCT Post ANC1 HIV testing, which
    will initially be pre-populated based on FY22 results from DATIM,
    but can be adjusted as needed. Red highlights indicate percentages
    over 100% or under 0%.

3.  Review Targeted ART Linkage Rates for linkage between HTS_TST: PMTCT
    Post ANC1, Positive and TX_NEW. This rate is locked in step with ART
    Linkage Rates set on the Cascade Tab, which default to 95%; return
    to that tab to adjust this rate, though note that this will alter
    linkage rates across all modalities.

4.  Review targets for HTS_TST: PMTCT Post ANC1, Positive, which are set
    by multiplying Total eligible for Post ANC1 retesting, set in step
    1, by the Yield rate set in step 2.

5.  Review targets for HTS_TST: PMTCT Post ANC1, Negative, which are set
    by subtracting HTS_TST: PMTCT Post ANC1, Positive from the Total
    eligible for Post ANC1 retesting set in step 1.

6.  Review modeled data for those tested and found positive for HIV post
    ANC1 who are linked to ART, set by multiplying those found positive
    by the Targeted ART Linkage Rate set in step 3, rounded to the
    nearest integer.**\
    **

## PMTCT: Testing Rationalization

```{r echo=FALSE, results='asis'}
sheet_name <- "PMTCT"
section <- "Testing Rationalization"
columns <- col_seq("AV", "BA")
data <- prepare_table_data(sheet_name, columns)
for (t in table_seq(data, max_col = 4)) {
  make_table(t, section)
  }
```

### DATIM Import

No data from this section will be imported into DATIM.

### Instructions

1.  Review Total PMTCT: Positives (From ANC1 & Post ANC1), which
    represents the *sum* of the PMTCT_STAT Known Positive, PMTCT_STAT
    Newly Tested Positive, and HTS_TST Post ANC1 Positive targets. This
    column serves as the starting point of the EID modeling process on
    the EID tab. For more information about the role of this data
    relative to EID targets, see that section of this User Guide.

2.  Use the remainder of this section of the PMTCT tab to analyze how
    PMTCT_STAT Newly Tested, Positives fit within the context of an
    overall testing strategy. In particular, consider how this modality
    contributes to total HTS_TST_POS in relation to HTS_INDEX, TB_STAT,
    and all other HTS modalities.

3.  Review any cases where this section is highlighted red, indicating
    over- or under-allocation of HTS_TST_POS targets across contributing
    modalities. While these allocation issues may be more the result of
    a different modality(ies), analysis of these to confirm no
    adjustments to PMTCT_STAT are warranted may prevent issues and
    additional work in other sections of the Target Setting Tool.

4.  Return to other tabs of the Target Setting Tool where issues flagged in this
    section require adjustment of either total HTS_TST_POS targets, or
    targets via other modalities. Similar Testing Rationalization
    sections can be also found in each of these other tabs of the
    Target Setting Tool. You may also use hyperlinks in column headers in this
    section to quickly navigate to the most relevant section of the
    Target Setting Tool.

\elandscape

\newpage