IDI Sampling Map

Abstract

Simple map of communties with the number of households and number of each of the 6 IDI groups in each and a tool to allow us to draw paths on them

Map

Below is an interactive map that plots all the communities we are working in.

• The size of the circle is proportional to the number of estimated compounds in each community.
  • Note: these are all compounds, based on the satellite data
  • Hover or click on a community to see the number of study households
• The color indicates the district (Karaga, Mion, Sagnarigu) with the the fill indcating whether we have at least one household in each of the 6 IDI groups
  • Hover over a circle to see the exact counts
• I have split the Risky arm into 3 groups. However, I used to different criteria reflected in the maps:
  • The split at 3 indicates any HHs > 3 are categorized as “high” (same for low)
  • For the split at 4/2, any HHs > 4 are categorized as “high” and any HHs < 2 are categorized as “low”

Note

Note: 832 / 1067 risky participants have completed all six draws (77%). 1529 / 1871 (82%) for all treated arms. This map only includes these people (all 6 draws).

```{python}
import folium
from folium.plugins import Draw


# Create a map centered on a location
m = folium.Map(
    location=[communities["centroid_lat"].mean(), communities["centroid_lon"].mean()],
    zoom_start=9,
)

m2 = folium.Map(
    location=[communities["centroid_lat"].mean(), communities["centroid_lon"].mean()],
    zoom_start=9,
)


# 3. Define a simple function to assign a color based on the 'category' column
def get_color(row, desaturate: bool):
    district = row["district"]
    if district.lower() == "karaga":
        color = "lightblue" if desaturate else "darkblue"
    elif district.lower() == "mion":
        color = "lightgreen" if desaturate else "darkgreen"
    elif district.lower() == "tolon":
        color = "grey" if desaturate else "black"
    else:
        color = "red" if desaturate else "darkred"
    return color


# 4. Loop through each row in the DataFrame to add a CircleMarker
for idx, row in communities.iterrows():
    radius = row["estimated_compounds"] * 3
    info_textm2 = f"""
            Community: {row["community"]}<br>
            Estimated Cpds: {row["estimated_compounds"]}<br>
            Households: {row["num_hh"]}<br>
            R_High: {row["risky_vhigh"]}<br>
            R_Bal: {row["risky_balanced"]}<br>
            R_Low: {row["risky_vlow"]}<br>
            Control: {row["control"]}<br>
            Pred : {row["predictable"]}<br>
            Stable: {row["stable"]}
            """

    desaturatem2 = (
        True
        if (
            (row["risky_vhigh"] > 0)
            & (row["risky_balanced"] > 0)
            & (row["risky_vlow"] > 0)
            & (row["control"] > 0)
            & (row["predictable"] > 0)
            & (row["stable"] > 0)
        )
        else False
    )
    fill = get_color(row, desaturatem2)
    border = get_color(row, desaturatem2)
    # Add the CircleMarker to the map
    folium.Circle(
        location=[row["centroid_lat"], row["centroid_lon"]],
        radius=radius,
        color=border,
        fill=True,
        fill_color=fill,
        fill_opacity=1,
        popup=info_textm2,
        tooltip=info_textm2,
    ).add_to(m2)

    info_text = f"""
            Community: {row["community"]}<br>
            Estimated Cpds: {row["estimated_compounds"]}<br>
            Households: {row["num_hh"]}<br>
            R_High: {row["risky_high"]}<br>
            R_Bal: {row["risky_balanced"]}<br>
            R_Low: {row["risky_low"]}<br>
            Control: {row["control"]}<br>
            Pred : {row["predictable"]}<br>
            Stable: {row["stable"]}
            """
    desaturate = (
        True
        if (
            (row["risky_high"] > 0)
            & (row["risky_balanced"] > 0)
            & (row["risky_low"] > 0)
            & (row["control"] > 0)
            & (row["predictable"] > 0)
            & (row["stable"] > 0)
        )
        else False
    )
    fill = get_color(row, desaturate)
    border = get_color(row, desaturate)
    folium.Circle(
        location=[row["centroid_lat"], row["centroid_lon"]],
        radius=radius,
        color=border,
        fill=True,
        fill_color=fill,
        fill_opacity=1,
        popup=info_text,
        tooltip=info_text,
    ).add_to(m)
```

Split at 3

```{python}
m
```

Make this Notebook Trusted to load map: File -> Trust Notebook

Split at 4 / 2

```{python}
m2
```

Make this Notebook Trusted to load map: File -> Trust Notebook

Data

```{python}
from itables import show

show(communities)
```

Loading ITables v2.5.2 from the internet... (need help?)