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• We examine the long-term ionospheric response to solar conditions from 2009–2019. • The trend in vTEC variations was in good accord with fluctuations in solar indices. • EUV flux has a better association with vTEC than F10.7 and SSN by 2% and 7%. • Solar variations of vTEC were dominated by their linear trends. • Predicted and observed vTEC measurements have moderately good agreement. In this research, we examine the long-term ionospheric response to solar conditions from 2009 - 2019 using GPS-TEC observations from 8 stations in East Africa at low/equatorial latitudes. To determine the effects of solar activity on ionospheric vertical-Total-Electron-Content (vTEC), solar proxies (EUV, F10.7, and SSN) were used. We have applied statistical analysis and used quadratic fits with solar indices to find the types of trends, forecast vTEC, and describe the daily, monthly, and seasonal variations of vTEC. We stated the fluctuations and dependency of GPS-vTEC on solar activity. From seasonal analysis, the greater values of GPS-vTEC were observed in the equinox's season from 2009–2016, followed by the December and June solstices, respectively. The highest values of GPS-vTEC were recorded in the years 2014 (70 and 67 TECU), 2013 (57 and 65 TECU), 2012 (56 and 60 TECU) at the March and September equinoxes, and the 2015 March equinox (68 TECU), and the lowest value of GPS-vTEC was recorded (2–3 TECU) for all seasons from 03 to 07 EAT. The changes in vTEC have confirmed worthy agreement with the changes in solar parameters, and EUV flux has a stronger association with vTEC than the F10.7 and SSN by 2% and 7%, respectively. Daily and monthly variations of vTEC showed positive associations with the solar parameters (EUV, F10.7, and SSN) from 2009–2019. We got both linear and nonlinear trends; however, when we approximated (EUV) 2 , (F 10.7) 2 , and (SSN) 2 coefficients, linear trends in vTEC were dominant. This analysis confirms that a quadratic polynomial can well capture the long-term solar activity dependency of vTEC in a statistical sense; based on the anticipated and observed vTEC values, the modeled outcome is suitable using EUV, F10.7, and SSN indices. But the modeled result is better using EUV and F10.7 than SSN in the region. In the predictions of vTEC, the maximum deviations and number of errors were observed during solar maxima years for EUV, F10.7, and SSN compared with the deviations and number of errors in solar minima years. Therefore, F10.7 is a better proxy of EUV flux in solar cycle 24 using monthly values, and the EUV flux is a better controller of GPS-vTEC changes compared to F10.7 and SSN, even if F10.7 is a proxy of EUV based on daily values. [ABSTRACT FROM AUTHOR]