(A) Flow diagram representing the natural history of Plasmodium falciparum infections in human populations. Uninfected individuals (S) can be infected at rate λ, with the probability of developing …
Depicts the age distribution of the simulated individuals.
Displays the simultaneous fit to 4 measured relationships between age and clinical immunity. The black dots refer to the data points offering a measurement for clinical immunity in each of these …
The black dots depict the data points in the Guerra et al. (2007) database. The colored dots show 100 thousand individual model predictions for the observable prevalence in a village (aggregated …
Compares the predicted clinical malaria case incidence for varying levels of prevalence (red), with the data (black) published in Patil et al. (2009). Much like in the previous figure, 100 thousand …
Shows how the distribution of malaria clinical cases across age bins changes with increasing all-age true prevalence.
The black triangles and dots refer to the prevalence measured at baseline and at month 12 post MDA in the MDA trials performed in the Thai-Myanmar border (Landier et al., 2018). We refrained from …
The box plots show the median and interquartile ranges of the proportional reduction in malaria prevalence for all simulated parameter sets. Each parameter set consists of a combination of initial …
Model outcome (measured as the proportional decrease in parasite prevalence) sensitivity to logistical (Teams – speed of coverage, and number of MDA campaigns), epidemiological (initial mean …
Intervention outcome sensitivity to spatial transmission heterogeneity in settings with different population mobility patterns. The vectorial capacity distributions associated with these simulations …
Model predicted interaction of logistical MDA considerations (speed of coverage – teams) with different population mobility levels (given in black background over each panel) in determining …
In all similar to Figure 2, it shows how the different model parameters modulate the predicted proportional decrease in artemisinin resistance after MDA. Negative numbers then reflect a rise in …
Illustrates how human population mobility (y-axis) interacts with how transmission risk is distributed over space (colored groups) to modulate the extent to which artemisinin resistance is able to …
Demonstrates under what conditions using 400 implementation teams is preferable over 15 teams when deploying an MDA campaign. We investigate different epidemiological contexts, characterized by …
Illustrates the interaction between human population mobility, seasonality patterns, and MDA operational parameters (number of teams and campaign start time). Colors indicate the proportion of …
Shows how the relationship between human population mobility (rows), seasonality patterns (blocks of columns), MDA operational parameters – number of teams (block of rows), campaigns and campaign …
Illustrates how a lower infectiousness assumption for asymptomatic malaria (red line) drives the likelihood of malaria elimination up for independently of the remaining model parameters.
These surface plots show the proportion of simulations (out of 100) in which elimination was achieved within a 5 year time horizon. Hypothetical interventions that decrease the vectorial capacity by …
These surface plots show a drastic improvement in transmission reduction impact when comparing implementations of MDA in setting with varying vector control (VC), against VC only intervention …
Illustrates the likelihood of elimination within 5 years of an elimination strategy consisting of 3 MDA rounds and a vector control strategy sustained over 1 year. We compare elimination prospects …
The same as in Figure 5, except that vector control is extended to last 5 years.
Factor | Meaning | Values |
---|---|---|
Teams | Number of teams performing prevalence surveys and distributing ACTs simultaneously. Translated into coverage speed in square brackets, that is, the number of days it takes to perform one MDA round in a region of 1000 villages. | 15 [267] 25 [160] 50 [80] 100 [40] 200 [20] 400 [10] |
Prevalence | Mean initial malaria u-PCR prevalence across all villages. | 0.5, 0.1, 0.15, 0.2, 0.25, 0.3 |
Resistance | Mean initial proportion of parasites which are artemisinin resistant. | 0.1, 0.2, 0.3 |
Distribution | Transmission heterogeneity distribution, underlying spatial heterogeneity of malaria transmission, manifested by differential mosquito density distributions. | Gaussian, Log-normal, Pareto |
Mobility | Describes the intensity of population movement in the general population. Indicates the per person average daily probability of moving to places other than their home village for short-term visits (see Mobility section in the Simulation Protocol). that is a population of individuals whose short-term movement occurs on average 25 times per year (25/365) has a relatively static population with low mobility. | 5/365 25/365 125/365 250/365 |
Campaigns | The number of MDA Campaigns | 1, 2 |
Peaks | The number of annual seasonal peaks | 1, 2 |
# | Name | Description | Value | Reference |
---|---|---|---|---|
1 | V | Set of villages | |V| = 1000 | |
2 | N | Set of individuals across all villages | |N| = 314,795 | - |
3 | ml | Proportion of males in the population | 0.48 | (National Institute of Statistics, 2008) |
4 | maxage | Maximum age | 80 years | - |
5 | beta | Biting rate | variable* | - |
6 | previ | Initial proportion of infectious people | variable* | - |
7 | resit | Initial proportion of artemisinin resistant infections | variable* | - |
8 | netuse | Proportion of individuals that own an insecticide treated bed net | 0.5 | - |
9 | itneffect | proportional decrease of individual susceptibility/infectiousness related to ITN usage | 0.2 | - |
10 | ovstay | Mean number of nights spent somewhere when undertaking short-term population movement | 3 | - |
11 | crit | Critical distance below which overnight stays somewhere other than your home are made very unlikely | 4 km | - |
12 | timecomp | Mean time to complete ACT routine treatment | 4 days | Best guess |
13 | fullcourse | Proportion that receives treatment full course | 0.8 | (Yeung et al., 2008) |
14 | covab | Proportion of symptomatic cases that receive antimalarials | 0.6 | (Yeung et al., 2008) |
15 | nomp | Relative probability of receiving treatment in a non-malaria post village | 0.1 | Best guess |
16 | asymtreat | Relative probability of receiving treatment without clinical symptom | 10−4 | - |
17 | tauab | Daily probability of receiving ACT in a village under MDA | 1/1.5 | - |
18 | gamma | Mean liver stage duration | 5 days | (Collins and Jeffery, 1999; Eyles and Young, 1951) |
19 | sigma | Mean time to infectiousness after liver emergence | 15 days | (Jeffery and Eyles, 1955) |
20 | mellow | Mean duration of symptoms | 3 days | (Church et al., 1997) |
21 | xa0 | Daily probability of going below the minimum effective artemisinin concentration | 1/7 | (Karbwang et al., 1998) |
22 | xai | Daily probability losing the DHA effect as part of ACT | 1/3 | (Rijken et al., 2011; Tarning et al., 2008) |
23 | xab | Daily probability of going below the minimum effective piperaquine concentration | 1/30 | (Rijken et al., 2011; Tarning et al., 2008) |
24 | xpr | Daily probability of going below the minimum effective primaquine concentration | 1/2 | (Burgess and Bray, 1961) |
25 | delta | Mean duration of a malaria untreated infection | 160 days | (Eyles and Young, 1951; Babiker et al., 1998; Franks et al., 2001) |
26 | imm_min | Minimum clinical immunity period | 40 days | Best guess |
27 | alpha | Average permanence in each immunity level | 60 days | - |
28 | phic | Relative infectiousness of symptomatic infections compared to sub-patent ones | 1 | - |
29 | mdi | Mosquito daily probability of dying while infectious | 1/7 | (Dawes et al., 2009) |
30 | mdn | Mosquito daily probability of dying while infected but not yet infectious | 1/20 | (Dawes et al., 2009) |
31 | mgamma | Mean extrinsic incubation period | 14 days | (Smith et al., 2014) |
32 | amp | Amplitude of mosquito density seasonal variation | 0.6 | Best guess |
33 | process | Days needed to administer a full ACT course in one village | 4 days | Optimistic guess |
34 | rounds | Number of drug rounds in an MDA campaign | 3 | Standard practice |
35 | btrounds | Number of days between drug rounds in an MDA campaign | 32 | Standard practice |
36 | vcefficacy | Vector control efficacy | variable* | - |
37 | Daily probability of clearing blood stage drug sensitive parasites with circulating dha | 1/5 | (Adjuik et al., 2004; Pukrittayakamee et al., 2004) | |
38 | Daily probability of clearing blood stage artemisinin resistant parasites with dha | 0.27* (0.05) | (Dondorp et al., 2009) | |
39 | Daily probability of clearing infectious stage drug sensitive parasites with circulating dha | 1/3 | (Adjuik et al., 2004; Pukrittayakamee et al., 2004) | |
40 | Daily probability of clearing infectious stage artemisinin resistant parasites with dha | 0.27* (0.09) | (Dondorp et al., 2009) | |
41 | Daily probability of clearing blood stage drug sensitive parasites with circulating dha- piperaquine | 1/3 | (Adjuik et al., 2004; Pukrittayakamee et al., 2004) | |
42 | Daily probability of clearing blood stage artemisinin resistant parasites with dha- piperaquine | 0.27* + (1.0–0.27)* (0.33) | (Dondorp et al., 2009) | |
43 | Daily probability of clearing infectious stage drug sensitive parasites with circulating dha- piperaquine | 1/3 | (Bustos et al., 2013) | |
44 | Daily probability of clearing infectious stage artemisinin resistant parasites with dha- piperaquine | 0.27* + (1.0–0.27)* (0.126) | - | |
45 | Daily probability of clearing blood stage drug sensitive parasites with circulating piperaquine | 1/3 | (Chen et al., 1982) | |
46 | Daily probability of clearing blood stage artemisinin resistant parasites with piperaquine | 1/3 | (Chen et al., 1982) | |
47 | Daily probability of clearing infectious stage drug sensitive parasites with circulating piperaquine | 1/20 | (Myint et al., 2007) | |
48 | Daily probability of clearing infectious stage artemisinin resistant parasites with piperaquine | 1/20 | (Myint et al., 2007) | |
49 | Daily probability of clearing infectious stage drug sensitive parasites with primaquine | 1/1.5 | (Burgess and Bray, 1961; Smithuis et al., 2010) | |
50 | Daily probability of clearing infectious stage artemisinin resistant parasites with primaquine | 1/1.5 | - | |
51 | k | Steepness of susceptibility increase with age | 0.14 | (Aguas et al., 2008) |
52 | r | Amplitude of susceptibility increase with age | 0.99 | (Aguas et al., 2008) |
*the values are varied in different simulation settings. Their values are given in the description of each set of experiments and the set of possible values is given in Table 1.